+publisher:"University of Saskatchewan" +contributor:("Li, Longhai")

University of Saskatchewan

1. Dong, Yue. A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models.

Degree: 2016, University of Saskatchewan

► When modelling count data, it is possible to have excessive zeros in the data in many applications. My thesis concentrates on the variable selection in… (more)

▼ When modelling count data, it is possible to have excessive zeros in the data in many applications. My thesis concentrates on the variable selection in zero-inflated Poisson (ZIP) models. This thesis work is motivated by Brown et al. (2015), who considered the excessive amount of zero in their data structure and the site-specific random effects, and used Bayesian LASSO method for variable selection in their post-fire tree recruitment study in interior Alaska, USA and north Yukon, Canada. However, the above study has not carried out systematic simulation studies to evaluate Bayesian LASSO’s performance under different scenarios. Therefore, my thesis conducts a series of simulation studies to evaluate Bayesian LASSO’s performance with respect to different setting of some simulation factors. My thesis considers three simulation factors: the number of subjects (N), the number of repeated measurements (R) and the true values of regression coefficients in the ZIP models. With different settings of the three factors, the proposed Bayesian LASSO’s performance would be evaluated using three indicators: the sensitivity, the specificity and the exact fit rate. For applied practitioners, my thesis would be a useful example demonstrating under what circumstances one can expect Bayesian LASSO to have good performance in ZIP models. After sorting out the simulation results, we can find that Bayesian LASSO’s performance is jointly affected by all the three simulation factors, while this method of variable selection is more reliable when the true coefficients are not close to zero. My thesis also has some limitations. Primarily, with the time limitation of my thesis, it is impossible to consider all the factors that can potentially affect the simulation results, and using other penalty forms other than L1 penalty is also left for future researchers to work on. Moreover, the current variable selection method is only for fixed effects selection while the variable selection for the mixed effect selection in ZIP models can be a direction for future work. Advisors/Committee Members: Liu, Juxin, Li, Longhai, Sowa, Artur, Lamb, Eric.

Subjects/Keywords: Variable selection; Zero-inflated model; Bayesian LASSO

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APA (6^th Edition):

Dong, Y. (2016). A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Dong, Yue. “A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models.” 2016. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Dong, Yue. “A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models.” 2016. Web. 20 Sep 2020.

Vancouver:

Dong Y. A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dong Y. A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Achath, Sudhakar 1955-. Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability.

Degree: 2017, University of Saskatchewan

URL: http://hdl.handle.net/10388/7889

► This study is about developing some further ideas in imprecise probability models of financial risk measures. A financial risk measure has been interpreted as an… (more)

Subjects/Keywords: Imprecise Probability; Lower Prevision; Risk Measure; Coherence

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APA (6^th Edition):

Achath, S. 1. (2017). Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7889

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Achath, Sudhakar 1955-. “Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability.” 2017. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7889.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Achath, Sudhakar 1955-. “Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability.” 2017. Web. 20 Sep 2020.

Vancouver:

Achath S1. Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability. [Internet] [Thesis]. University of Saskatchewan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7889.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Achath S1. Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability. [Thesis]. University of Saskatchewan; 2017. Available from: http://hdl.handle.net/10388/7889

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

3. Wang, Xiaoying. Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data.

Degree: 2019, University of Saskatchewan

URL: http://hdl.handle.net/10388/11952

► Background: Recent advances in next-generation sequencing (NGS) technology enable researchers to collect a large volume of microbiome data. Microbiome data consist of operational taxonomic unit… (more)

▼ Background: Recent advances in next-generation sequencing (NGS) technology enable researchers to collect a large volume of microbiome data. Microbiome data consist of operational taxonomic unit (OTU) count data characterized by zero-inflation, over-dispersion, and grouping structure among the sample. Currently, statistical testing methods based on generalized linear mixed effect models (GLMM) are commonly performed to identify OTUs that are associated with a phenotype such as human diseases or plant traits. There are a number of limitations for statistical testing methods including these two: (1) the validity of p-value/q-value depends sensitively on the correctness of models, and (2) the statistical significance does not necessarily imply predictivity. Statistic testing methods depend on model correctness and attempt to select ”marginally relevant” features, not the most predictive ones. Predictive analysis using methods such as LASSO is an alternative approach for feature selection. To the best of our knowledge, this approach has not been used widely for analyzing microbiome data. Methodology: We use four synthetic datasets simulated from zero-inflated negative binomial distribution and a real human gut microbiome data to compare the feature selection performance of LASSO with the likelihood ratio test methods applied to GLMMs. We also investigate the performance of cross-validation in estimating the out-of-sample predictivity of selected features in zero-inflated data. Results: Our studies with synthetic datasets show that the feature selection performance of LASSO is remarkably excellent in zero-inflated data and is comparable with the likelihood ratio test applied to the true data generating model. The feature selection performance of LASSO is better when the distributions of counts are more differentiated by the phenotype, which is a categorical variable in our synthetic datasets. In addition, we performed LOOCV on the train set and out-of-sample prediction on the test set. The performance of the cross-validatory (CV) predictive measures are very close to the out-of-sample predictivity measures. This indicates that LOOCV predictive metrics provide honest measures of the predictivity of the features selected by LASSO. Therefore, the CV predictive measures are good guidance for choosing cutoffs (shrinkage parameter λ) in selecting features with LASSO. By contrast, when wrong models are fitted to a dataset, the differences between the q-values and the actual false discovery rates are huge; hence, their q-values are tremendously misleading for selecting features. Our comparison of LASSO and statistical testing methods (likelihood ratio test in our analysis) in the real dataset shows that small q-values do not necessarily imply high predictivity of the selected OTUs. However, the researchers often use q-values to find the predictors. That is why we need to look at q-values carefully. Conclusions: Statistical testing methods perform greatly in zero-inflated datasets on both synthetic and real… Advisors/Committee Members: Li, Longhai, Liu, Juxin, Wang, Jiun-Chau, Yang, Jian.

Subjects/Keywords: Generalized Linear Mixed Model; Least Absolute Shrinkage and Selection Operator; Likelihood Ratio Test; False Discovery Rate; Leave-One-Out Cross-Validation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Wang, X. (2019). Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/11952

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wang, Xiaoying. “Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data.” 2019. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/11952.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wang, Xiaoying. “Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data.” 2019. Web. 20 Sep 2020.

Vancouver:

Wang X. Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data. [Internet] [Thesis]. University of Saskatchewan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/11952.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang X. Comparison of Statistical Testing and Predictive Analysis Methods for Feature Selection in Zero-inflated Microbiome Data. [Thesis]. University of Saskatchewan; 2019. Available from: http://hdl.handle.net/10388/11952

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

4. Achath, Sudhakar 1955-. Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability.

Degree: 2017, University of Saskatchewan

URL: http://hdl.handle.net/10388/7888

► This study is about developing some further ideas in imprecise probability models of financial risk measures. A financial risk measure has been interpreted as an… (more)

Subjects/Keywords: Imprecise Probability; Lower Prevision; Risk Measure; Coherence

1 more image…

Record Details Similar Records Cite « Share

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Achath, S. 1. (2017). Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7888

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Achath, Sudhakar 1955-. “Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability.” 2017. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7888.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Achath, Sudhakar 1955-. “Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability.” 2017. Web. 20 Sep 2020.

Vancouver:

Achath S1. Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability. [Internet] [Thesis]. University of Saskatchewan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7888.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Achath S1. Computational Determination of Coherence of Financial Risk Measure as a Lower Prevision of Imprecise Probability. [Thesis]. University of Saskatchewan; 2017. Available from: http://hdl.handle.net/10388/7888

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

5. Rana, Md Masud. Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data.

Degree: 2012, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2012-08-636

► Spatial data (also called georeferenced data) arise in a wide range of scientific studies, including geography, agriculture, criminology, geology, urban and regional economics. The underlying… (more)

▼ Spatial data (also called georeferenced data) arise in a wide range of scientific studies, including geography, agriculture, criminology, geology, urban and regional economics. The underlying spatial effects – the measurement error caused by any spatial pattern embedded in data – may affect both the validity and robustness of traditional descriptive and inferential techniques. Therefore, it is of paramount importance to take into account spatial effects when analysing spatially dependent data. In particular, addressing the spatial association among attribute values observed at different locations and the systematic variation of phenomena by locations are the two major aspects of modelling spatial data. The bent-cable is a parametric regression model to study data that exhibits a trend change over time. It comprises two linear segments to describe the incoming and outgoing phases, joined by a quadratic bend to model the transition period. For spatial longitudinal data, measurements taken over time are nested within spatially dependent locations. In this thesis, we extend the existing longitudinal bent-cable regression model to handle spatial effects. We do so in a hierarchical Bayesian framework by allowing the error terms to be correlated across space. We illustrate our methodology with an application to atmospheric chlorofluorocarbon (CFC) data. We also present a simulation study to demonstrate the performance of our proposed methodology. Although we have tailored our work for the CFC data, our modelling framework may be applicable to a wide variety of other situations across the range of the econometrics, transportation, social, health and medical sciences. In addition, our methodology can be further extended by taking into account interaction between temporal and spatial effects. With the current model, this could be done with a spatial correlation structure that changes as a function of time. Advisors/Committee Members: Khan, Shahedul A., Li, Longhai, Guo, Xulin, Soteros, Chris, Bickis, Mikelis.

Subjects/Keywords: atmospheric ozone depletion; Bayesian inference; bent cable regression; chlorofluorocarbon; longitudinal data; spatial effects

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Rana, M. M. (2012). Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2012-08-636

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rana, Md Masud. “Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data.” 2012. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2012-08-636.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rana, Md Masud. “Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data.” 2012. Web. 20 Sep 2020.

Vancouver:

Rana MM. Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data. [Internet] [Thesis]. University of Saskatchewan; 2012. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2012-08-636.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rana MM. Spatial-Longitudinal Bent-Cable Model with an Application to Atmospheric CFC Data. [Thesis]. University of Saskatchewan; 2012. Available from: http://hdl.handle.net/10388/ETD-2012-08-636

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

6. Wu, Tingxuan 1987-. Randomized Survival Probability Residual for Assessing Parametric Survival Models.

Degree: 2018, University of Saskatchewan

URL: http://hdl.handle.net/10388/11696

► Traditional residuals for diagnosing accelerated failure time models in survival analysis, such as Cox-Snell, martingale and deviance residuals, have been widely used. However, ex- amining… (more)

Subjects/Keywords: RSP; UCS; MCS; NCS

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APA (6^th Edition):

Wu, T. 1. (2018). Randomized Survival Probability Residual for Assessing Parametric Survival Models. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/11696

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wu, Tingxuan 1987-. “Randomized Survival Probability Residual for Assessing Parametric Survival Models.” 2018. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/11696.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wu, Tingxuan 1987-. “Randomized Survival Probability Residual for Assessing Parametric Survival Models.” 2018. Web. 20 Sep 2020.

Vancouver:

Wu T1. Randomized Survival Probability Residual for Assessing Parametric Survival Models. [Internet] [Thesis]. University of Saskatchewan; 2018. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/11696.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu T1. Randomized Survival Probability Residual for Assessing Parametric Survival Models. [Thesis]. University of Saskatchewan; 2018. Available from: http://hdl.handle.net/10388/11696

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

7. Li, Zhaoqin. QUANTIFYING GRASSLAND NON-PHOTOSYNTHETIC VEGETATION BIOMASS USING REMOTE SENSING DATA.

Degree: 2017, University of Saskatchewan

URL: http://hdl.handle.net/10388/8130

► Non-photosynthetic vegetation (NPV) refers to vegetation that cannot perform a photosynthetic function. NPV, including standing dead vegetation and surface plant litter, plays a vital role… (more)

▼ Non-photosynthetic vegetation (NPV) refers to vegetation that cannot perform a photosynthetic function. NPV, including standing dead vegetation and surface plant litter, plays a vital role in maintaining ecosystem function through controlling carbon, water and nutrient uptake as well as natural fire frequency and intensity in diverse ecosystems such as forest, savannah, wetland, cropland, and grassland. Due to its ecological importance, NPV has been selected as an indicator of grassland ecosystem health by the Alberta Public Lands Administration in Canada. The ecological importance of NPV has driven considerable research on quantifying NPV biomass with remote sensing approaches in various ecosystems. Although remote images, especially hyperspectral images, have demonstrated potential for use in NPV estimation, there has not been a way to quantify NPV biomass in semiarid grasslands where NPV biomass is affected by green vegetation (PV), bare soil and biological soil crust (BSC). The purpose of this research is to find a solution to quantitatively estimate NPV biomass with remote sensing approaches in semiarid mixed grasslands. Research was conducted in Grasslands National Park (GNP), a parcel of semiarid mixed prairie grassland in southern Saskatchewan, Canada. Multispectral images, including newly operational Landsat 8 Operational Land Imager (OLI) and Sentinel-2A Multi-spectral Instrument (MSIs) images and fine Quad-pol Radarsat-2 images were used for estimating NPV biomass in early, middle, and peak growing seasons via a simple linear regression approach. The results indicate that multispectral Landsat 8 OLI and Sentinel-2A MSIs have potential to quantify NPV biomass in peak and early senescence growing seasons. Radarsat-2 can also provide a solution for NPV biomass estimation. However, the performance of Radarsat-2 images is greatly affected by incidence angle of the image acquisition. This research filled a critical gap in applying remote sensing approaches to quantify NPV biomass in grassland ecosystems. NPV biomass estimates and approaches for estimating NPV biomass will contribute to grassland ecosystem health assessment (EHA) and natural resource (i.e. land, soil, water, plant, and animal) management. Advisors/Committee Members: Guo, Xulin, Noble, Bram, de Boer, Dirk, Li, Longhai, Akkerman, Avi.

Subjects/Keywords: non-photosynthetic vegetation; biomass; green vegetation; biological soil crust; bare soil; multispectral image; Landsat 8; Sentinel-2A; Radarsat-2; ecosystem health; vegetation phenology

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APA (6^th Edition):

Li, Z. (2017). QUANTIFYING GRASSLAND NON-PHOTOSYNTHETIC VEGETATION BIOMASS USING REMOTE SENSING DATA. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/8130

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Li, Zhaoqin. “QUANTIFYING GRASSLAND NON-PHOTOSYNTHETIC VEGETATION BIOMASS USING REMOTE SENSING DATA.” 2017. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/8130.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Li, Zhaoqin. “QUANTIFYING GRASSLAND NON-PHOTOSYNTHETIC VEGETATION BIOMASS USING REMOTE SENSING DATA.” 2017. Web. 20 Sep 2020.

Vancouver:

Li Z. QUANTIFYING GRASSLAND NON-PHOTOSYNTHETIC VEGETATION BIOMASS USING REMOTE SENSING DATA. [Internet] [Thesis]. University of Saskatchewan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/8130.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li Z. QUANTIFYING GRASSLAND NON-PHOTOSYNTHETIC VEGETATION BIOMASS USING REMOTE SENSING DATA. [Thesis]. University of Saskatchewan; 2017. Available from: http://hdl.handle.net/10388/8130

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

8. Ashleik, Naeima Abdallah 1980-. Learning for Contingency Tables and Survival Data using Imprecise Probabilities.

Degree: 2018, University of Saskatchewan

URL: http://hdl.handle.net/10388/8501

► Bayesian inference is a method of statistical inference in which all forms of uncertainty are expressed in terms of probability. Classical Bayesian inference has some… (more)

▼ Bayesian inference is a method of statistical inference in which all forms of uncertainty are expressed in terms of probability. Classical Bayesian inference has some limitations. One of these situations is when we have little to no information about the experiment; another situation is when we have computational or time limitations. Also problematic is a situation where there are conflicts in choosing a prior distribution where we have experts giving different prior information, which results in less precise posterior probabilities. Because of these limitations, imprecise Bayesian approach takes place in Bayesian inference. Upper and lower posterior expectations are computed in order to calculate the degree of imprecision of the log-odds ratio. This is implemented in two-way contingency tables and then generalized to three-way tables by using different families of prior distributions, is which the core of this work. Survival data including right-censored observations are generated and converted to a sequence of 2 x 2 tables, three-way contingency tables, each 2 x 2 is built at each observed death time. Here, we assume only one death happens at each time and no ties. To implement imprecise Bayesian inference, two choices of imprecise priors are chosen. A set of four Normal priors and a set of four Beta priors are used with a non-central hypergeometric likelihood to update the posterior families and then the degree of imprecision is calculated for both cases. An example of real data is applied on Ovarian Cancer Survival data where upper and lower posterior expectations are estimated in order to calculate the degree of imprecision. We conduct simulation studies to sample from posterior distribution and estimate the log-odds ratio by using upper and lower posterior expectations. In the situation of three-way contingency tables, updating a set of priors to a set of posterior is done sequentially at each table by running MCMC method through using JAGS from R via rjags and runjags packages. Also, four factors (sample size, censoring rate, true parameter, and balancing rate) are studied to see how these four factors a ect the degree of imprecision with the two choices of imprecise priors. A fractional factorial design of 27 runs is constructed to see which one of these four factors is more signi cant. For each one of these 27 combination, upper and lower posterior expectations and the degree of imprecision of the log-odds ratio are calculated. The findings show that the smallest value of the degree of imprecision appears at the combination where the sample size is large (n = 200) and small number of censored times. In contrast, the largest value of the degree of imprecision is observed at the combination where the sample size is small (n = 40) and large number of censored times. These conclusions are supported by the findings of ANOVA that show that main e ects of the four factors are significant. The conclusion that can be summarized from the results of this work is having more information (more data) leads to less… Advisors/Committee Members: Bickis, Mike, Soteros, Chris, Khan, Shahedul, Li, Longhai, Neufeld, Eric.

Subjects/Keywords: Bayesian inference; Contingency tables; Survival Data; and Imprecise probability.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Ashleik, N. A. 1. (2018). Learning for Contingency Tables and Survival Data using Imprecise Probabilities. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/8501

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Ashleik, Naeima Abdallah 1980-. “Learning for Contingency Tables and Survival Data using Imprecise Probabilities.” 2018. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/8501.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Ashleik, Naeima Abdallah 1980-. “Learning for Contingency Tables and Survival Data using Imprecise Probabilities.” 2018. Web. 20 Sep 2020.

Vancouver:

Ashleik NA1. Learning for Contingency Tables and Survival Data using Imprecise Probabilities. [Internet] [Thesis]. University of Saskatchewan; 2018. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/8501.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ashleik NA1. Learning for Contingency Tables and Survival Data using Imprecise Probabilities. [Thesis]. University of Saskatchewan; 2018. Available from: http://hdl.handle.net/10388/8501

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

9. Rostamiforooshani, Mehdi 1988-. Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation Structure on the Parameter Estimates.

Degree: 2016, University of Saskatchewan

URL: http://hdl.handle.net/10388/7324

► In practice, survival data are often grouped into clusters, such as clinical sites, geographical regions and so on. This clustering imposes correlation among individuals within… (more)

▼ In practice, survival data are often grouped into clusters, such as clinical sites, geographical regions and so on. This clustering imposes correlation among individuals within each cluster, which is known as within cluster correlation. For instance, in our motivating example, within each long term care facility (LTCF), the elderly are likely from nearby areas with similar quality of life and having access to similar health care. As such, individual sharing the same hidden features may correlate with each other. The shared frailty model is therefore often used to take into account the correlation among individuals from the same cluster. In some applications, when the survival data are collected over geographical regions, random effects corresponding to geographical regions in closer proximately to each other might also be similar in magnitude, due to underlying environmental characteristics. Therefore, shared spatial frailty model can be adopted to model the spatial correlation among the clusters, which are often implemented using Bayesian Markov Chain Monte Carlo method. This method comes at the price of slow mixing rates and heavy computational cost, which may reader it impractical for data intensive application. In this thesis, motivated by the computational challenges encountered in modelling spatial correlation in a real application involving large scale survival data, we used simulations to assess the efficiency loss in parameter estimates if residual spatial correlation is present but using a spatially uncorrelated random effect term in the model. Our simulation study indicates that the share frailty model with only the spatially correlated random effect term may not be sufficient to govern the total residual variation, whereas the simpler model with only the spatially uncorrelated random effect term performs surprisingly well in estimating the model parameters compared with the true model with both the spatially correlated and uncorrelated random effect terms. As such, using the shared frailty model with independent frailty term should be reliable for estimating the effects of covariates, especially when the percentage of censoring is not high and the number of clusters is large. Also, such model is advantageous, since it can be easily and efficiently implemented in a standard statistical software. This is not to say that the shared frailty model with independent frailty term should be preferred over the spatial frailty model in all cases. Indeed, when the primary goal of inference is predicting the hazard for specific covariates group, additional care needs to be given due to the bias in the scale parameter associated with the Weibull distribution, when the correlation structure is misspecified. Advisors/Committee Members: Feng, Cindy Xin., Whiting, Susan, Li, Longhai, Guo, Xulin, Szafron, Michael.

Subjects/Keywords: Regression; Random-effect term; Likelihood function; Bias; Bayesian Statistics; MCMC

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APA (6^th Edition):

Rostamiforooshani, M. 1. (2016). Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation Structure on the Parameter Estimates. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rostamiforooshani, Mehdi 1988-. “Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation Structure on the Parameter Estimates.” 2016. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rostamiforooshani, Mehdi 1988-. “Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation Structure on the Parameter Estimates.” 2016. Web. 20 Sep 2020.

Vancouver:

Rostamiforooshani M1. Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation Structure on the Parameter Estimates. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rostamiforooshani M1. Modeling the Risk of Hip Fracture among Residents in the Long Term Care Facilities in British Columbia, Canada: Impact of Misspecication of the Correlation Structure on the Parameter Estimates. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

10. Maleki, Farhad 1981-. Sensitivity And Specificity Of Gene Set Analysis.

Degree: 2019, University of Saskatchewan

URL: http://hdl.handle.net/10388/12182

► High-throughput technologies are widely used for understanding biological processes. Gene set analysis is a well-established computational approach for providing a concise biological interpretation of high-throughput… (more)

▼ High-throughput technologies are widely used for understanding biological processes. Gene set analysis is a well-established computational approach for providing a concise biological interpretation of high-throughput gene expression data. Gene set analysis utilizes the available knowledge about the groups of genes involved in cellular processes or functions. Large collections of such groups of genes, referred to as gene set databases, are available through online repositories to facilitate gene set analysis. There are a large number of gene set analysis methods available, and current recommendations and guidelines about the method of choice for a given experiment are often inconsistent and contradictory. It has also been reported that some gene set analysis methods suffer from a lack of specificity. Furthermore, the sheer size of gene set databases makes it difficult to study these databases and their effect on gene set analysis. In this thesis, we propose quantitative approaches for the study of reproducibility, sensitivity, and specificity of gene set analysis methods; characterize gene set databases; and offer guidelines for choosing an appropriate gene set database for a given experiment. We review commonly used gene set analysis methods; classify these methods based on their components; describe the underlying requirements and assumptions for each class; suggest the appropriate method to be used for a given experiment; and explain the challenges and pitfalls in interpreting results for each class of methods. We propose a methodology and use it for evaluating the effect of sample size on the results of thirteen gene set analysis methods utilizing real datasets. Further, to investigate the effect of method choice on the results of gene set analysis, we develop a quantitative approach and use it to evaluate ten commonly used gene set analysis methods. We also quantify and visualize gene set overlap and study its effect on the specificity of over-representation analysis. We propose Silver, a quantitative framework for simulating gene expression datasets and evaluating gene set analysis methods without relying on oversimplifying assumptions commonly made when evaluating gene set analysis methods. Finally, we propose a systematic approach to select appropriate gene set databases for conducting gene set analysis for a given experiment. Using this approach, we highlight the drawbacks of meta-databases such as MSigDB, a well-established gene set database made by extracting gene sets from several sources including GO, KEGG, Reactome, and BioCarta. Our findings suggest that the results of most gene set analysis methods are not reproducible for small sample sizes. In addition, the results of gene set analysis significantly vary depending on the method used, with little to no commonality between the 20 most significant results. We show that there is a significant negative correlation between gene set overlap and the specificity of over-representation analysis. This suggests that gene set overlap should be taken into… Advisors/Committee Members: Kusalik, Anthony J, McQuillan, Ian, Links, Matthew, Vassileva, Julita, Li, Longhai.

Subjects/Keywords: Gene set analysis; Enrichment analysis; Gene set databases; Gene set overlap; Gene expression

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APA (6^th Edition):

Maleki, F. 1. (2019). Sensitivity And Specificity Of Gene Set Analysis. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/12182

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Maleki, Farhad 1981-. “Sensitivity And Specificity Of Gene Set Analysis.” 2019. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/12182.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Maleki, Farhad 1981-. “Sensitivity And Specificity Of Gene Set Analysis.” 2019. Web. 20 Sep 2020.

Vancouver:

Maleki F1. Sensitivity And Specificity Of Gene Set Analysis. [Internet] [Thesis]. University of Saskatchewan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/12182.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Maleki F1. Sensitivity And Specificity Of Gene Set Analysis. [Thesis]. University of Saskatchewan; 2019. Available from: http://hdl.handle.net/10388/12182

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

11. Sajobi, Tolulope. Descriptive discriminant analysis for repeated measures data.

Degree: 2012, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2012-03-361

► Background: Linear discriminant analysis (DA) encompasses procedures for classifying observations into groups (predictive discriminant analysis, PDA) and describing the relative importance of variables for distinguishing… (more)

▼ Background: Linear discriminant analysis (DA) encompasses procedures for classifying observations into groups (predictive discriminant analysis, PDA) and describing the relative importance of variables for distinguishing between groups (descriptive discriminant analysis, DDA) in multivariate data. In recent years, there has been increased interest in DA procedures for repeated measures data. PDA procedures that assume parsimonious repeated measures mean and covariance structures have been developed, but corresponding DDA procedures have not been proposed. Most DA procedures for repeated measures data rest on the assumption of multivariate normality, which may not be satisfied in biostatistical applications. For example, health-related quality of life (HRQOL) measures, which are increasingly being used as outcomes in clinical trials and cohort studies, are likely to exhibit skewed or heavy-tailed distributions. As well, measures of relative importance based on discriminant function coefficients (DFCs) for DDA procedures have not been proposed for repeated measures data. Purpose: The purpose of this research is to develop repeated measures discriminant analysis (RMDA) procedures based on parsimonious covariance structures, including compound symmetric and first order autoregressive structures, and that are robust (i.e., insensitive) to multivariate non-normal distributions. It also extends these methods to evaluate the relative importance of variables in multivariate repeated measures (i.e., doubly multivariate) data. Method: Monte Carlo studies were conducted to investigate the performance of the proposed RMDA procedures under various degrees of group mean separation, repeated measures correlation structures, departure from multivariate normality, and magnitude of covariance mis-specification. Data from the Manitoba Inflammatory Bowel Disease Cohort Study, a prospective longitudinal cohort study about the psychosocial determinants of health and well-being, are used to illustrate their applications. Results: The conventional maximum likelihood (ML) estimates of DFCs for RMDA procedures based on parsimonious covariance structures exhibited substantial bias and error when the covariance structure was mis-specified or when the data followed a multivariate skewed or heavy-tailed distribution. The DFCs of RMDA procedures based on robust estimators obtained from coordinatewise trimmed means and Winsorized variances, were less biased and more efficient when the data followed a multivariate non-normal distribution, but were sensitive to the effects of covariance mis-specification. Measures of relative importance for doubly multivariate data based on linear combinations of the within-variable DFCs resulted in the highest proportion of correctly ranked variables. Conclusions: DA procedures based on parsimonious covariance structures and robust estimators will produce unbiased and efficient estimates of variable relative importance of variables in repeated measures data and can be used to test for change in relative importance… Advisors/Committee Members: Lix, Lisa M., Muhajarine, Nazeem, Laverty, William, Jones, Jennifer, Li, Longhai.

Subjects/Keywords: discriminant analysis; repeated measurements; covariance structure; health-related quality of life

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sajobi, T. (2012). Descriptive discriminant analysis for repeated measures data. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2012-03-361

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sajobi, Tolulope. “Descriptive discriminant analysis for repeated measures data.” 2012. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2012-03-361.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sajobi, Tolulope. “Descriptive discriminant analysis for repeated measures data.” 2012. Web. 20 Sep 2020.

Vancouver:

Sajobi T. Descriptive discriminant analysis for repeated measures data. [Internet] [Thesis]. University of Saskatchewan; 2012. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2012-03-361.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sajobi T. Descriptive discriminant analysis for repeated measures data. [Thesis]. University of Saskatchewan; 2012. Available from: http://hdl.handle.net/10388/ETD-2012-03-361

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

12. Soltani Farsani, Jafar. Statistical power of epidemiological studies of low dose levels of ionizing radiation and cancer.

Degree: 2020, University of Saskatchewan

URL: http://hdl.handle.net/10388/12819

► The purpose of this research is to inspect the statistical power of studies that investigate the effects of low dose ionizing radiation on the incidence… (more)

Subjects/Keywords: Statistical power; Ionizing radiation; Score test statistic

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APA (6^th Edition):

Soltani Farsani, J. (2020). Statistical power of epidemiological studies of low dose levels of ionizing radiation and cancer. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/12819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Soltani Farsani, Jafar. “Statistical power of epidemiological studies of low dose levels of ionizing radiation and cancer.” 2020. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/12819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Soltani Farsani, Jafar. “Statistical power of epidemiological studies of low dose levels of ionizing radiation and cancer.” 2020. Web. 20 Sep 2020.

Vancouver:

Soltani Farsani J. Statistical power of epidemiological studies of low dose levels of ionizing radiation and cancer. [Internet] [Thesis]. University of Saskatchewan; 2020. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/12819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Soltani Farsani J. Statistical power of epidemiological studies of low dose levels of ionizing radiation and cancer. [Thesis]. University of Saskatchewan; 2020. Available from: http://hdl.handle.net/10388/12819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

13. Qiu, Shi. Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping.

Degree: 2015, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2015-03-1988

► The well-documented problems associated with mapping raw rates of disease have resulted in an increased use of Bayesian hierarchical models to produce maps of "smoothed''… (more)

Subjects/Keywords: cross-validation; disease mapping; importance sampling; WAIC

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APA (6^th Edition):

Qiu, S. (2015). Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2015-03-1988

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Qiu, Shi. “Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping.” 2015. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2015-03-1988.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Qiu, Shi. “Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping.” 2015. Web. 20 Sep 2020.

Vancouver:

Qiu S. Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping. [Internet] [Thesis]. University of Saskatchewan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2015-03-1988.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Qiu S. Cross-validatory Model Comparison and Divergent Regions Detection using iIS and iWAIC for Disease Mapping. [Thesis]. University of Saskatchewan; 2015. Available from: http://hdl.handle.net/10388/ETD-2015-03-1988

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

14. Kendall, Courtney. Factor scoring methods affected by response shift in patient-reported outcomes.

Degree: 2014, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2014-07-1626

► Objective: Patient-reported outcomes (PROs) are measures collected from a patient to determine how he/she feels or functions in regards to a health condition. Longitudinal PROs,… (more)

▼ Objective: Patient-reported outcomes (PROs) are measures collected from a patient to determine how he/she feels or functions in regards to a health condition. Longitudinal PROs, which are collected at multiple occasions from the same individual, may be affected by response shift (RS). RS is a change in a person’s self-evaluation of a target construct. Latent variable models (LVMs) are statistical models that relate observed variables to latent variables (LV). LVMs are used to analyze PROs and detect RS. LVs are random variables whose realizations are not observable. Factor scores are estimates of LVs for each individual and can be estimated from parameter estimates of LVMs. Factor scoring methods to estimate factor scores include: Thurstone, Bartlett, and sum scores. This simulation study examines the effects of RS on factor scores used to test for change in the LV means and recommend a factor scoring method least affected by RS. Methods: Data from two time points were fit to three confirmatory factor analysis (CFA) models. CFA models are a type of LVM. Each CFA model had different sets of parameters that were invariant over time. The unconstrained (Uncon) CFA model had no invariant parameters, the constrained (Con) model had all the parameters invariant, and the partially constrained (Pcon) model had some of the parameters invariant over time. Factor scores were estimated and tested for change over time via paired t-test. The Type I error, power, and factor loading (the regression coefficient between an observed and LV) and factor score bias were estimated to determine if RS influenced the test of change over time and factor score estimation. Results: The results depended on the true LV mean. The Type I error and power were similar for all factor scoring methods and CFA models when the LV mean was 0 at time 1. For LV mean of 0.5 at time 1 the Type I error and power increased as RS increased for all factor scores except for scores estimated from the Uncon model and Bartlett method. The biases of the factor loadings were unaffected by RS when estimated from an Uncon model. The factor scores estimated from the Uncon model and the Bartlett and sum scores method had the smallest factor score biases. Conclusion: The factor scores estimated from the Uncon model and the Bartlett method was least affected by RS and performed best in all measures of Type I error, statistical power, factor loading and factor score bias. Estimating factor scores from PROs data that ignores RS may result in erroneous (or biased) estimates. Advisors/Committee Members: Lix, Lisa, Liu, Juxin, Li, Longhai, Sarty, Gordon, Martin, John.

Subjects/Keywords: Factor scores; response shift,; patient-reported outcomes

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APA (6^th Edition):

Kendall, C. (2014). Factor scoring methods affected by response shift in patient-reported outcomes. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2014-07-1626

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kendall, Courtney. “Factor scoring methods affected by response shift in patient-reported outcomes.” 2014. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2014-07-1626.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kendall, Courtney. “Factor scoring methods affected by response shift in patient-reported outcomes.” 2014. Web. 20 Sep 2020.

Vancouver:

Kendall C. Factor scoring methods affected by response shift in patient-reported outcomes. [Internet] [Thesis]. University of Saskatchewan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2014-07-1626.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kendall C. Factor scoring methods affected by response shift in patient-reported outcomes. [Thesis]. University of Saskatchewan; 2014. Available from: http://hdl.handle.net/10388/ETD-2014-07-1626

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

15. Jiang, Lai. Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure.

Degree: 2015, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2015-09-2232

► Feature selection is demanded in many modern scientific research problems that use high-dimensional data. A typical example is to find the genes that are most… (more)

▼ Feature selection is demanded in many modern scientific research problems that use high-dimensional data. A typical example is to find the genes that are most related to a certain disease (e.g., cancer) from high-dimensional gene expression profiles. There are tremendous difficulties in eliminating a large number of useless or redundant features. The expression levels of genes have structure; for example, a group of co-regulated genes that have similar biological functions tend to have similar mRNA expression levels. Many statistical methods have been proposed to take the grouping structure into consideration in feature selection and regression, including Group LASSO, Supervised Group LASSO, and regression on group representatives. In this thesis, we propose to use a sophisticated Markov chain Monte Carlo method (Hamiltonian Monte Carlo with restricted Gibbs sampling) to fit T-probit regression with heavy-tailed priors to make selection in the features with grouping structure. We will refer to this method as fully Bayesian T-probit. The main feature of fully Bayesian T-probit is that it can make feature selection within groups automatically without a pre-specification of the grouping structure and more efficiently discard noise features than LASSO (Least Absolute Shrinkage and Selection Operator). Therefore, the feature subsets selected by fully Bayesian T-probit are significantly more sparse than subsets selected by many other methods in the literature. Such succinct feature subsets are much easier to interpret or understand based on existing biological knowledge and further experimental investigations. In this thesis, we use simulated and real datasets to demonstrate that the predictive performances of the more sparse feature subsets selected by fully Bayesian T-probit are comparable with the much larger feature subsets selected by plain LASSO, Group LASSO, Supervised Group LASSO, random forest, penalized logistic regression and t-test. In addition, we demonstrate that the succinct feature subsets selected by fully Bayesian T-probit have significantly better predictive power than the feature subsets of the same size taken from the top features selected by the aforementioned methods. Advisors/Committee Members: Li, Longhai, Bickis, Mik, Liu, Juxin, Kusalik, Anthony, Stephens, David.

Subjects/Keywords: Bayesian methods; probit; MCMC; gene expression data; grouping structure

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APA (6^th Edition):

Jiang, L. (2015). Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2015-09-2232

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Jiang, Lai. “Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure.” 2015. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2015-09-2232.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Jiang, Lai. “Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure.” 2015. Web. 20 Sep 2020.

Vancouver:

Jiang L. Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure. [Internet] [Thesis]. University of Saskatchewan; 2015. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2015-09-2232.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jiang L. Fully Bayesian T-probit Regression with Heavy-tailed Priors for Selection in High-Dimensional Features with Grouping Structure. [Thesis]. University of Saskatchewan; 2015. Available from: http://hdl.handle.net/10388/ETD-2015-09-2232

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

16. Wang, Yunyang 1986-. Comparison of Stochastic Volatility Models Using Integrated Information Criteria.

Degree: 2016, University of Saskatchewan

URL: http://hdl.handle.net/10388/7591

► Stochastic volatility (SV) models are a family of models that commonly used in the modeling of stock prices. In all SV models, volatility is treated… (more)

▼ Stochastic volatility (SV) models are a family of models that commonly used in the modeling of stock prices. In all SV models, volatility is treated as a stochastic time series. However, SV models are still quite different from each other from the perspective of both underlying principles and parameter layouts. Therefore, selecting the most appropriate SV model for a given set of stock price data is important in making future predictions of stock market. To achieve this goal, leave-one-out cross-validation (LOOCV) methods could be used. However, LOOCV methods are computationally expensive, thus its use is very limited in practice. In our studies of SV models, we proposed two new model-selection approaches, integrated widely applicable information criterion (iWAIC) and integrated importance sampling information criterion (iIS-IC), as alternatives to approximate LOOCV results. In iWAIC and iIS-IC methods, we first calculate the expected likelihood of each observation as an integral with respect to the corresponding latent variable (the current log-volatility parameter). Since the observations are highly correlated with their corresponding latent variable, the integrated likelihood of each t^th observation (y_t^obs) is expected to approximate the expect likelihood of y_t^obs calculated from the model with y_t^obs as its holdout data. Second, the integrated expected likelihood is used, as a replacement of the expected likelihood, in the calculation of information criteria. Since the integration with respect to the latent variable largely reduces the model's bias towards the corresponding observation, the integrated information criteria are expected to approximate LOOCV results. To evaluate the performance of iWAIC and iIS-IC, we first conducted an empirical study using simulated data sets. The results from this study show that iIS-IC method has an improved performance over the traditional IS-IC, but iWAIC does not outperform the non-integrated WAIC method. A further empirical study using real-world stock market return data was subsequently carried out. According to the model-selection results, the best model for the given data is either the SV model with two independent autoregressive processes, or the SV model with nonzero expected returns. Advisors/Committee Members: Li, Longhai, Samei, Ebrahim, Liu, Juxin, Chaban, Maxym.

Subjects/Keywords: Model selection criteria; Stochastic volatility models; Integrated information criteria

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APA (6^th Edition):

Wang, Y. 1. (2016). Comparison of Stochastic Volatility Models Using Integrated Information Criteria. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7591

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wang, Yunyang 1986-. “Comparison of Stochastic Volatility Models Using Integrated Information Criteria.” 2016. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7591.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wang, Yunyang 1986-. “Comparison of Stochastic Volatility Models Using Integrated Information Criteria.” 2016. Web. 20 Sep 2020.

Vancouver:

Wang Y1. Comparison of Stochastic Volatility Models Using Integrated Information Criteria. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7591.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang Y1. Comparison of Stochastic Volatility Models Using Integrated Information Criteria. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7591

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

17. Dong, Mei. Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease.

Degree: 2019, University of Saskatchewan

URL: http://hdl.handle.net/10388/12118

► In the context of identifying related SNPs for a phenotype of interest (e.g., a disease status), we consider the problem of assessing the predictivity of… (more)

▼ In the context of identifying related SNPs for a phenotype of interest (e.g., a disease status), we consider the problem of assessing the predictivity of SNPs that are selected by performing genome-wide association studies. Internal cross-validation (ICV) is a wrong but often used method for this assessment. With ICV, a subset of SNPs are pre-selected based on all samples then cross-validation (CV) is applied to assess the predictivity of the pre-selected SNPs. The predictivity estimate of the selected SNPs given by ICV is upwardly biased. This is often called the feature selection bias problem. The cause of this bias is that the feature selection procedure, which is a part of training procedure, is not external to the test samples in ICV. A correct method, called external cross-validation (ECV), is to re-select features based on only the training samples in each fold of CV such that the feature selection is external to test samples. The feature selection bias of ICV has been discussed by a few articles in the context of cancer diagnosis with microarray data. However, this problem has not received sufficient attention in the literature, especially in the context of predicting with SNP data. Many articles in the literature use ICV or do not state explicitly that their feature selection is external to test samples. In this thesis, we use an example of predicting late-onset Alzheimer's disease (LOAD) from selected SNPs to demonstrate that ICV could lead to severe false discovery. We use a real SNP dataset related to LOAD and two synthetic datasets (simulated response with real SNPs) for this demonstration. For the prediction, we compare the performances of three regularized logistic regression methods: LASSO, elastic-net, and a fully Bayesian hyper-LASSO method. For the LOAD dataset, we see that, except for APOE, no other SNPs can improve the prediction of LOAD using ECV method; however, the predictivity estimate of selected SNPs given by ICV can reach an R² as high as 80%. For the synthetic datasets, we obtain the similar results as in the real dataset; additionally we see that the predictivity estimate of selected SNPs obtained with ICV can be even higher than the oracle predictivity of the truly related SNPs used to generate the response. In this study, we also find that the hyper-LASSO method can achieve better predictive performance than the LASSO and elastic-net. We recommend that ICV should not be used to measure the predictivity of selected SNPs and this statement should be made clear in research articles. Advisors/Committee Members: Li, Longhai, Balbuena, Lloyd, Feng, Cindy, Wu, Fangxiang, Wang, JC.

Subjects/Keywords: Feature Selection bias; Cross-validation; Predictive Analysis; GWAS; Alzheimer's Disease

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APA (6^th Edition):

Dong, M. (2019). Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/12118

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Dong, Mei. “Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease.” 2019. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/12118.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Dong, Mei. “Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease.” 2019. Web. 20 Sep 2020.

Vancouver:

Dong M. Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease. [Internet] [Thesis]. University of Saskatchewan; 2019. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/12118.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dong M. Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease. [Thesis]. University of Saskatchewan; 2019. Available from: http://hdl.handle.net/10388/12118

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

18. Islam, Naorin. Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects.

Degree: 2016, University of Saskatchewan

URL: http://hdl.handle.net/10388/7632

► Background of the Study. Repeated use of a substance (alcohol or drug) may lead to mental and physical sickness, personality changes, insomnia, nausea, mood swings… (more)

▼ Background of the Study. Repeated use of a substance (alcohol or drug) may lead to mental and physical sickness, personality changes, insomnia, nausea, mood swings and other disturbances. The number of people addicted to alcohol and/or drug has been increasing every year at an alarming rate. Although the extent of abuse is not directly measurable (i.e., latent), statistical techniques allow us to describe such a hypothetical construct using available information. Objective. There are many factors potentially associated with substance abuse (e.g., smoking, education, cultural background). Although these variables are readily available in many studies, the cause (e.g., a measure of drug or alcohol abuse) is latent, with the observed variables being its manifestations. A measure of a latent health factor index could also be of particular interest. In this study, we investigate the effects of socio-demographic variables on substance (drug and alcohol) abuse and health in the Canadian population. In particular, the objective is to address the following questions: (a) What would be a reasonable hypothesis to explain causes of substance abusive behavior (i.e., cause and effect relationship)? (b) What model would adequately describe the cause-and-effect relationship between the observed variables and health and substance-related latent variables? (c) What covariates are significantly associated with alcohol and drug abusive environments and health status? Method. To describe the cause-and-effect relationship among substance abuse, health and socio-demographic variables, we consider structural equation modeling. One of the appealing features of this technique is that it provides a concise assessment of complex relationships. The idea is to formulate a hypothesis regarding such relationships based on prior knowledge about the problem at hand, and then evaluate this hypothesis using statistical techniques. The main goal is to develop a model/hypothesis which can adequately describe the interrelationships among these variables. Summary Results. The study is based on a survey conducted by Health Canada. We consider 2012 survey data for Saskatchewan and Manitoba, and then develop models to describe the complex relationships among three hypothetical constructs (drug and alcohol abusive environments and heath) and socio-demographic variables. One of the important findings of the study is that an increase in the severity of drug abusive environment may worsen the health of individuals. Another interesting finding is that smoking has no direct effect on health, but it may lead to an environment (alcohol or drug abusive) that could have negative impact on health. Based on our findings, we conclude that substance abuse may significantly deteriorate health. This research will provide policy-makers as well as the public with an understanding of the extent of impacts of substance abuse and relevant socio-demographic variables on health. Advisors/Committee Members: Khan, Shahedul, Li, Longhai, Srinivasan, Raj, Guo, Xulin.

Subjects/Keywords: Structural equation modeling

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APA (6^th Edition):

Islam, N. (2016). Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7632

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Islam, Naorin. “Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects.” 2016. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7632.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Islam, Naorin. “Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects.” 2016. Web. 20 Sep 2020.

Vancouver:

Islam N. Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7632.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Islam N. Substance Abuse and Health: A Structural Equation Modeling Approach to Assess Latent Health Effects. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7632

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

19. Bai, Wei. Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data.

Degree: 2018, University of Saskatchewan

URL: http://hdl.handle.net/10388/9216

► In microbiome research, it is often of interest to investigate the impact of clinical and environmental factors on microbial abundance, which is often quantified as… (more)

▼ In microbiome research, it is often of interest to investigate the impact of clinical and environmental factors on microbial abundance, which is often quantified as the total number of unique operational taxonomic units (OTUs). The important features of OTU count data are the presence of a large number of zeros and skewness in the positive counts. A common strategy to handle excessive zeros is to use zero-inflated models or zero-modified (hurdle) models. Moreover, subjects in microbiome data often have clustering structure, for example humans from the same family or plants from the same plot; as a result, random effects should be included to account for the clustering effects. Model diagnosis is an essential step to ensure that a fitted model is adequate for the data. However, diagnosing zero-inflated counts models is still a challenging research problem. Pearson and deviance residuals are often used in practice for diagnosing counts models, despite wide recognition that these residuals are far from normality when applied to count data. Randomized quantile residual (RQR) was proposed in literature to circumvent the above problems in traditional residuals. The key idea of the RQR is to randomize the lower tail probability into a uniform random number between the discontinuity gap of cumulative density function (CDF). It can be shown that RQRs are normally distributed under the true model. To the best of our knowledge, RQR has not been applied to diagnose zero inflated or modified mixed effects models. In this thesis project, we have developed generic R functions that can compute RQRs for zero-inflated and zero-modified mixed effects models based on fitting outputs of glmmTMB. We have tested our functions using datasets generated from zero-modified Poisson (ZMP) and zero-modified negative binomial (ZMNB) models. Our simulation studies show that RQRs are normally distributed under the true model. In GOF tests, the type 1 error rates are close to the nominal level 0.05, and the powers of rejecting the wrong models are very good. We have also applied RQR to assess 8 models for a real human microbiome OTU dataset and concluded that ZMNB or zero-inflated negative binomial (ZINB) models provide adequate fits to the dataset. Advisors/Committee Members: Li, Longhai, Feng, Cindy, Khan, Shahedul, Wright, Laura.

Subjects/Keywords: Operational taxonomic units (OTUs); randomized quantile residual (RQR); cumulative density function (CDF); zero-modified Poisson (ZMP); zero-modified negative binomial (ZMNB); zero-inflated negative binomial (ZINB).

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Bai, W. (2018). Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/9216

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bai, Wei. “Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data.” 2018. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/9216.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bai, Wei. “Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data.” 2018. Web. 20 Sep 2020.

Vancouver:

Bai W. Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data. [Internet] [Thesis]. University of Saskatchewan; 2018. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/9216.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bai W. Randomized Quantile Residual for Assessing Generalized Linear Mixed Models with Application to Zero-Inflated Microbiome Data. [Thesis]. University of Saskatchewan; 2018. Available from: http://hdl.handle.net/10388/9216

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

20. ABDULLAH CHISTI, K B M. Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist.

Degree: 2013, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2013-08-1194

► The purpose of this study is to determine the correlation between texture features of Di raction Enhanced Imaging (DEI) images and trabecular properties of human… (more)

▼ The purpose of this study is to determine the correlation between texture features of Di raction Enhanced Imaging (DEI) images and trabecular properties of human wrist bone in the assessment of osteoporosis. Osteoporosis is a metabolic bone disorder that is characterized by reduced bone mass and a deterioration of bone structure which results in an increased fracture risk. Since the disease is preventable, diagnostic techniques are of major importance. Bone micro-architecture and Bone mineral density (BMD) are two main factors related to osteoporotic fractures. Trabecular properties like bone volume (BV), trabecular number (Tb.N), trabecular thickness (Tb.Th), bone surface (BS), and other properties of bone, characterizes the bone architecture. Currently, however, BMD is the only measurement carried out to assess osteoporosis. Researchers suggest that bone micro-architecture and texture analysis of bone images along with BMD can provide more accuracy in the assessment. We have applied texture analysis on DEI images and extracted texture features. In our study, we used fractal analysis, gray level co-occurrence matrix (GLCM), texture feature coding method (TFCM), and local binary patterns (LBP) as texture analysis methods to extract texture features. 3D Micro-CT trabecular properties were extracted using SkyScanTM CTAN software. Then, we determined the correlation between texture features and trabecular properties. GLCM energy fea- ture of DEI images explained more than 39% of variance in bone surface by volume ratio (BS/BV), 38% of variance in percent bone volume (BV/TV), and 37% of variance in trabecular number (Tb.N). TFCM homogeneity feature of DEI images explained more than 42% of variance in bone surface (BS) parameter. LBP operator - LBP 11 of DEI images explained more than 34% of vari- ance in bone surface (BS) and 30% of variance in bone surface density (BS/TV). Fractal dimension parameter of DEI images explained more than 47% of variance in bone surface (BS) and 32% of variance in bone volume (BV). This study will facilitate in the quanti cation of osteoporosis beyond conventional BMD. Advisors/Committee Members: Eramian, Mark, Cooper, David, Neufeld, Eric, Chapman, Dean, Li, Longhai.

Subjects/Keywords: Texture; Osteoporosis; TFCM; GLCM; LBP; Fractal; Bone micro architecture; DEI

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APA (6^th Edition):

ABDULLAH CHISTI, K. B. M. (2013). Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2013-08-1194

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

ABDULLAH CHISTI, K B M. “Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist.” 2013. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2013-08-1194.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

ABDULLAH CHISTI, K B M. “Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist.” 2013. Web. 20 Sep 2020.

Vancouver:

ABDULLAH CHISTI KBM. Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist. [Internet] [Thesis]. University of Saskatchewan; 2013. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2013-08-1194.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

ABDULLAH CHISTI KBM. Texture Analysis of Diffraction Enhanced Synchrotron Images of Trabecular Bone at the Wrist. [Thesis]. University of Saskatchewan; 2013. Available from: http://hdl.handle.net/10388/ETD-2013-08-1194

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

21. Rijal, Sanjeev 1979-. Complex Survey And Design Effect With Rao-Scott Correction And Log-Linear Analysis.

Degree: 2017, University of Saskatchewan

URL: http://hdl.handle.net/10388/7975

► Collection of data through sample surveys involves a wide range of techniques and procedures. Data is collected with the priority of maximum accuracy of information… (more)

Subjects/Keywords: Design Effect; Rao-Scott Correction; Simultaneous Test Procedure

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APA (6^th Edition):

Rijal, S. 1. (2017). Complex Survey And Design Effect With Rao-Scott Correction And Log-Linear Analysis. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7975

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rijal, Sanjeev 1979-. “Complex Survey And Design Effect With Rao-Scott Correction And Log-Linear Analysis.” 2017. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7975.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rijal, Sanjeev 1979-. “Complex Survey And Design Effect With Rao-Scott Correction And Log-Linear Analysis.” 2017. Web. 20 Sep 2020.

Vancouver:

Rijal S1. Complex Survey And Design Effect With Rao-Scott Correction And Log-Linear Analysis. [Internet] [Thesis]. University of Saskatchewan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7975.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rijal S1. Complex Survey And Design Effect With Rao-Scott Correction And Log-Linear Analysis. [Thesis]. University of Saskatchewan; 2017. Available from: http://hdl.handle.net/10388/7975

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

22. Sadeghpour, Alireza. Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models.

Degree: 2016, University of Saskatchewan

URL: http://hdl.handle.net/10388/7513

► Traditional tools for model diagnosis for Generalized Linear Model (GLM), such as deviance and Pearson residuals, have been often utilized to examine goodness of fit… (more)

▼ Traditional tools for model diagnosis for Generalized Linear Model (GLM), such as deviance and Pearson residuals, have been often utilized to examine goodness of fit of GLMs. In normal linear regression, both of these residuals coincide and are normally distributed; however in non-normal regression models, such as Logistic or Poisson regressions, the residuals are far from normality, with residuals aligning nearly parallel curves according to distinct response values, which imposes great challenges for visual inspection. As such, the residual plots for modeling discrete outcome variables convey very limited meaningful information, which render it of limited practical use. Randomized quantile residuals was proposed in literature to circumvent the above-mentioned problems in the traditional residuals in modeling discrete outcomes. However, this approach has not gained deserved awareness and attention. Therefore, in this thesis, we theoretically justify the normality of the randomized quantile residuals and compare their performance with the traditional ones, Pearson and deviance residuals, through a set of simulation studies. Our simulation studies demonstrate the normality of randomized quantile residuals when the fitted model is true. Further, we show that randomized quantile residual is able to detect many kinds of model inadequacies. For instance, the linearity assumption of the covariate effect in GLM can be examined by visually checking the plots of randomized quantile residuals against the predicted values or the covariates. Randomized quantile residuals can be also used to detect overdispersion and zero-inflation, two commonly occurred cases associated with count data. We advocate examining normality of the randomized quantile residuals as a unifying way for examining the goodness of fit for regression model, especially for modeling the discrete outcomes. We also demonstrate this approach in a real application studying the independent association between air pollution and daily influenza incidence in Beijing, China. Advisors/Committee Members: Li, Longhai, Feng, Cindy, Khan, Shahedul, Samei, Ebrahim, Eramian, Mark.

Subjects/Keywords: Regression; GLM; Residual; Pearson; Deviance; Randomized Quantile; ZIP

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sadeghpour, A. (2016). Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7513

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sadeghpour, Alireza. “Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models.” 2016. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7513.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sadeghpour, Alireza. “Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models.” 2016. Web. 20 Sep 2020.

Vancouver:

Sadeghpour A. Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7513.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sadeghpour A. Empirical Investigation of Randomized Quantile Residuals for Diagnosis of Non-Normal Regression Models. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7513

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

23. Wang, Yunyang 1986-. Comparison of Stochastic Volatility Models Using Integrated Information Criteria.

Degree: 2016, University of Saskatchewan

URL: http://hdl.handle.net/10388/7590

► Stochastic volatility (SV) models are a family of models that commonly used in the modeling of stock prices. In all SV models, volatility is treated… (more)

▼ Stochastic volatility (SV) models are a family of models that commonly used in the modeling of stock prices. In all SV models, volatility is treated as a stochastic time series. However, SV models are still quite different from each other from the perspective of both underlying principles and parameter layouts. Therefore, selecting the most appropriate SV model for a given set of stock price data is important in making future predictions of stock market. To achieve this goal, leave-one-out cross-validation (LOOCV) methods could be used. However, LOOCV methods are computationally expensive, thus its use is very limited in practice. In our studies of SV models, we proposed two new model-selection approaches, integrated widely applicable information criterion (iWAIC) and integrated importance sampling information criterion (iIS-IC), as alternatives to approximate LOOCV results. In iWAIC and iIS-IC methods, we first calculate the expected likelihood of each observation as an integral with respect to the corresponding latent variable (the current log-volatility parameter). Since the observations are highly correlated with their corresponding latent variable, the integrated likelihood of each t^th observation (y_t^obs) is expected to approximate the expect likelihood of y_t^obs calculated from the model with y_t^obs as its holdout data. Second, the integrated expected likelihood is used, as a replacement of the expected likelihood, in the calculation of information criteria. Since the integration with respect to the latent variable largely reduces the model's bias towards the corresponding observation, the integrated information criteria are expected to approximate LOOCV results. To evaluate the performance of iWAIC and iIS-IC, we first conducted an empirical study using simulated data sets. The results from this study show that iIS-IC method has an improved performance over the traditional IS-IC, but iWAIC does not outperform the non-integrated WAIC method. A further empirical study using real-world stock market return data was subsequently carried out. According to the model-selection results, the best model for the given data is either the SV model with two independent autoregressive processes, or the SV model with nonzero expected returns. Advisors/Committee Members: Li, Longhai, Samei, Ebrahim, Liu, Juxin, Chaban, Maxym.

Subjects/Keywords: Model selection criteria; Stochastic volatility models; Integrated information criteria

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APA (6^th Edition):

Wang, Y. 1. (2016). Comparison of Stochastic Volatility Models Using Integrated Information Criteria. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7590

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wang, Yunyang 1986-. “Comparison of Stochastic Volatility Models Using Integrated Information Criteria.” 2016. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/7590.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wang, Yunyang 1986-. “Comparison of Stochastic Volatility Models Using Integrated Information Criteria.” 2016. Web. 20 Sep 2020.

Vancouver:

Wang Y1. Comparison of Stochastic Volatility Models Using Integrated Information Criteria. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/7590.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang Y1. Comparison of Stochastic Volatility Models Using Integrated Information Criteria. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7590

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

24. Kar, Setu Chandra. Generalized Bent-Cable Methodology for Changepoint Data: A Bayesian Approach.

Degree: 2017, University of Saskatchewan

URL: http://hdl.handle.net/10388/8313

► The choice of the model framework in a regression setting depends on the nature of the data. The focus of this study is on changepoint… (more)

▼ The choice of the model framework in a regression setting depends on the nature of the data. The focus of this study is on changepoint data, exhibiting three phases: incoming and outgoing, both of which are linear, joined by a curved transition. These types of data can arise in many applications, including medical, health and environmental sciences. Piecewise linear models have been extensively utilized to characterize such changepoint trajectories in di erent scientific fields. However, although appealing due to its simple structure, a piecewise linear model is not realistic in many applications where data exhibit a gradual change over time. The most important aspect of characterizing a changepoint trajectory involves identifying the transition zone accurately. It is not only because the location of the transition zone is of particular interest in many areas of study, but also because it plays an important role in adequately describing the incoming and the outgoing phases of a changepoint trajectory. Note that once the transition is detected, the incoming and the outgoing phases can be modeled using linear functions. Overall, it is desirable to formulate a model in such a way that it can capture all the three phases satisfactorily, while being parsimonious with greatly interpretable regression coe cients. Since data may exhibit an either gradual or abrupt transition, it is also important for the transition model to be flexible. Bent-cable regression is an appealing statistical tool to characterize such trajectories, quantifying the nature of the transition between the two linear phases by modeling the transition as a quadratic phase with unknown width. We demonstrate that a quadratic function may not be appropriate to adequately describe many changepoint data. In practice, the quadratic function of the bent-cable model may lead to a wider or narrower interval than what could possibly be necessary to adequately describe a transition phase. We propose a generalization of the bent-cable model by relaxing the assumption of the quadratic bend. Specifically, an additional transition parameter is included in the bent-cable model to provide su cient flexibility so that inference about the transition zone (i.e., shape and width of the bend) can be data driven, rather than pre-assumed as a specific type. We discuss the properties of the generalized model, and then propose a Bayesian approach for statistical inference. The generalized model is then demonstrated with applications to three data sets taken from environmental science and economics. We also consider a comparison among the quadratic bent-cable, generalized bent-cable and piecewise linear models in terms of goodness of fit in analyzing both real-world and simulated data. Moreover, we supplement the motivation for our generalized bent-cable methodology via extensive simulations – we simulate changepoint data under some realistic assumptions, and then fit the quadratic bent-cable, generalized bent-cable and piecewise linear models to each of the simulated data sets to… Advisors/Committee Members: Khan, Shahedul Ahsan, Li, Longhai, Samei, Ebrahim, Chaban, Maxym.

Subjects/Keywords: Bayesian; bent-cable; changepoint; Markov Chain Monte Carlo; transition

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APA (6^th Edition):

Kar, S. C. (2017). Generalized Bent-Cable Methodology for Changepoint Data: A Bayesian Approach. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/8313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kar, Setu Chandra. “Generalized Bent-Cable Methodology for Changepoint Data: A Bayesian Approach.” 2017. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/8313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kar, Setu Chandra. “Generalized Bent-Cable Methodology for Changepoint Data: A Bayesian Approach.” 2017. Web. 20 Sep 2020.

Vancouver:

Kar SC. Generalized Bent-Cable Methodology for Changepoint Data: A Bayesian Approach. [Internet] [Thesis]. University of Saskatchewan; 2017. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/8313.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kar SC. Generalized Bent-Cable Methodology for Changepoint Data: A Bayesian Approach. [Thesis]. University of Saskatchewan; 2017. Available from: http://hdl.handle.net/10388/8313

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

25. Naseri, Mahsa. A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS.

Degree: 2013, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2013-12-1419

► In service-oriented environments, services are put together in the form of a workflow with the aim of distributed problem solving. Capturing the execution details of… (more)

▼ In service-oriented environments, services are put together in the form of a workflow with the aim of distributed problem solving. Capturing the execution details of the services' transformations is a significant advantage of using workflows. These execution details, referred to as provenance information, are usually traced automatically and stored in provenance stores. Provenance data contains the data recorded by a workflow engine during a workflow execution. It identifies what data is passed between services, which services are involved, and how results are eventually generated for particular sets of input values. Provenance information is of great importance and has found its way through areas in computer science such as: Bioinformatics, database, social, sensor networks, etc. Current exploitation and application of provenance data is very limited as provenance systems started being developed for specific applications. Thus, applying learning and knowledge discovery methods to provenance data can provide rich and useful information on workflows and services. Therefore, in this work, the challenges with workflows and services are studied to discover the possibilities and benefits of providing solutions by using provenance data. A multifunctional architecture is presented which addresses the workflow and service issues by exploiting provenance data. These challenges include workflow composition, abstract workflow selection, refinement, evaluation, and graph model extraction. The specific contribution of the proposed architecture is its novelty in providing a basis for taking advantage of the previous execution details of services and workflows along with artificial intelligence and knowledge management techniques to resolve the major challenges regarding workflows. The presented architecture is application-independent and could be deployed in any area. The requirements for such an architecture along with its building components are discussed. Furthermore, the responsibility of the components, related works and the implementation details of the architecture along with each component are presented. Advisors/Committee Members: Ludwig, Simone A., Osgood, Nathaniel, Horsch, Michael, McCalla, Gord, Li, Longhai.

Subjects/Keywords: Workflow; Provenance; Worflow Evaluation; Service Composition; Service Selection; Hidden Markov Model; Partially Observable Markov Decision Process; Bayesian Structure Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Naseri, M. (2013). A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2013-12-1419

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Naseri, Mahsa. “A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS.” 2013. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2013-12-1419.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Naseri, Mahsa. “A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS.” 2013. Web. 20 Sep 2020.

Vancouver:

Naseri M. A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS. [Internet] [Thesis]. University of Saskatchewan; 2013. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2013-12-1419.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Naseri M. A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS. [Thesis]. University of Saskatchewan; 2013. Available from: http://hdl.handle.net/10388/ETD-2013-12-1419

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

26. Obeidat, Mohammed. Bayesian analysis for time series of count data.

Degree: 2014, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2014-07-1589

► Time series involving count data are present in a wide variety of applications. In many applications, the observed counts are usually small and dependent. Failure… (more)

▼ Time series involving count data are present in a wide variety of applications. In many applications, the observed counts are usually small and dependent. Failure to take these facts into account can lead to misleading inferences and may detect false relationships. To tackle such issues, a Poisson parameter-driven model is assumed for the time series at hand. This model can account for the time dependence between observations through introducing an autoregressive latent process. In this thesis, we consider Bayesian approaches for estimating the Poisson parameter-driven model. The main challenge is that the likelihood function for the observed counts involves a high dimensional integral after integrating out the latent variables. The main contributions of this thesis are threefold. First, I develop a new single-move (SM) Markov chain Monte Carlo (MCMC) method to sample the latent variables one by one. Second, I adopt the idea of the particle Gibbs sampler (PGS) method \citep{andrieu} into our model setting and compare its performance with the SM method. Third, I consider Bayesian composite likelihood methods and compare three different adjustment methods with the unadjusted method and the SM method. The comparisons provide a practical guide to what method to use. We conduct simulation studies to compare the latter two methods with the SM method. We conclude that the SM method outperforms the PGS method for small sample size, while they perform almost the same for large sample size. However, the SM method is much faster than the PGS method. The adjusted Bayesian composite methods provide closer results to the SM than the unadjusted one. The PGS and the selected adjustment method from simulation studies are compared with the SM method via a real data example. Similar results are obtained: first, the PGS method provides results very close to those of the SM method. Second, the adjusted composite likelihood methods provide closer results to the SM than the unadjusted one. Advisors/Committee Members: Liu, Juxin, Soteros, Chrisine, Bickis, Mik, Li, Longhai, Osgood, Nathaniel, Gao, Xin.

Subjects/Keywords: Time series; count data; Poisson parameter-driven model; composite likelihood; particle Gibbs sampler; car crashes

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Obeidat, M. (2014). Bayesian analysis for time series of count data. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2014-07-1589

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Obeidat, Mohammed. “Bayesian analysis for time series of count data.” 2014. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2014-07-1589.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Obeidat, Mohammed. “Bayesian analysis for time series of count data.” 2014. Web. 20 Sep 2020.

Vancouver:

Obeidat M. Bayesian analysis for time series of count data. [Internet] [Thesis]. University of Saskatchewan; 2014. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2014-07-1589.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Obeidat M. Bayesian analysis for time series of count data. [Thesis]. University of Saskatchewan; 2014. Available from: http://hdl.handle.net/10388/ETD-2014-07-1589

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

27. Schmirler, Matthew. Strand Passage And Knotting Probabilities In An Interacting Self-Avoiding Polygon Model.

Degree: 2012, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2012-09-670

► The work presented in this thesis develops a new model for local strand passage in a ring polymer in a dilute salt solution. This model,… (more)

▼ The work presented in this thesis develops a new model for local strand passage in a ring polymer in a dilute salt solution. This model, called the Interacting Local Strand Passage (ILSP) model, models ring polymers via Theta-SAPs, which are self-avoiding polygons (SAPs) in the simple cubic lattice that contain a fixed structure Theta. This fixed structure represents two segments of the self-avoiding polygon being brought ''close'' together for the purpose of performing a strand passage. Theta-SAPs were first studied in the Local Strand Passage (LSP) model developed by Szafron (2000, 2009), where each Theta-SAP is considered equally likely in order to model good solvent conditions. In the ILSP model, each Theta-SAP has a modified Yukawa potential energy which contains an attractive term as well as a screened Coulomb potential that accounts for the effect of salt in the model. The energy function used in this model was first proposed by Tesi et al. (1994) for studying self-avoiding polygons in the simple cubic lattice. The ILSP model is studied in this thesis using the Interacting Theta-BFACF (I-Theta-BFACF) Algorithm, an algorithm which is developed in this thesis and is proven to be ergodic on the set of all Theta-SAPs of a particular knot type and connection class. The I-Theta-BFACF algorithm was created by modifying the Theta-BFACF algorithm developed by Szafron (2000, 2009) to include energy-based Metropolis sampling. This modification allows one to sample Theta-SAPs of a particular knot type and connection class based on a priori chosen solvent conditions. Multiple simulations (each consisting of 40 billion time steps) of composite Markov Chain Monte Carlo implementations of the I-Theta-BFACF algorithm are performed on unknotted connection class II Theta-SAPs over a wide range of salt concentrations. The data from these simulations is used to estimate, as a function of polygon length, the probability of an unknotted Theta-SAP remaining an unknot after a strand passage, as well as the probability of it becoming a positive trefoil knot. The results strongly suggest that as the length of a Theta-SAP goes to infinity, the probability of the Theta-SAP becoming knotted after a strand passage increases as the salt concentration in the model increases. These results serve as a first step for studying how the knot reduction factor (studied by Liu et al. (2006) and Szafron and Soteros (2011)) of a ring polymer varies in differing solvent conditions. The goal of this future research is to find solvent conditions and a local geometry of the strand passage site that yields a knot reduction factor comparable to the research of Rybenkov et al. (1997), which shows an 80-fold reduction of knotting after type II topoisomerase enzymes act on DNA. Advisors/Committee Members: Soteros, Christine E., Bickis, Miķelis G., Szafron, Michael L., Li, Longhai, Kusalik, Anthony J..

Subjects/Keywords: Mathematics; Statistics; Topoisomerase; MCMC; Markov Chain Monte Carlo; Metropolis Sampling; DNA; Self Avoiding Polygons

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Schmirler, M. (2012). Strand Passage And Knotting Probabilities In An Interacting Self-Avoiding Polygon Model. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2012-09-670

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Schmirler, Matthew. “Strand Passage And Knotting Probabilities In An Interacting Self-Avoiding Polygon Model.” 2012. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2012-09-670.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Schmirler, Matthew. “Strand Passage And Knotting Probabilities In An Interacting Self-Avoiding Polygon Model.” 2012. Web. 20 Sep 2020.

Vancouver:

Schmirler M. Strand Passage And Knotting Probabilities In An Interacting Self-Avoiding Polygon Model. [Internet] [Thesis]. University of Saskatchewan; 2012. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2012-09-670.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Schmirler M. Strand Passage And Knotting Probabilities In An Interacting Self-Avoiding Polygon Model. [Thesis]. University of Saskatchewan; 2012. Available from: http://hdl.handle.net/10388/ETD-2012-09-670

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

28. Janzen, Michael. Virtual camera selection using a semiring constraint satisfaction approach.

Degree: 2012, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2012-06-417

► Players and viewers of three-dimensional computer generated games and worlds view renderings from the viewpoint of a virtual camera. As such, determining a good view… (more)

Subjects/Keywords: virutal camera selection; SCSP

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Janzen, M. (2012). Virtual camera selection using a semiring constraint satisfaction approach. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2012-06-417

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Janzen, Michael. “Virtual camera selection using a semiring constraint satisfaction approach.” 2012. Thesis, University of Saskatchewan. Accessed September 20, 2020. http://hdl.handle.net/10388/ETD-2012-06-417.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Janzen, Michael. “Virtual camera selection using a semiring constraint satisfaction approach.” 2012. Web. 20 Sep 2020.

Vancouver:

Janzen M. Virtual camera selection using a semiring constraint satisfaction approach. [Internet] [Thesis]. University of Saskatchewan; 2012. [cited 2020 Sep 20]. Available from: http://hdl.handle.net/10388/ETD-2012-06-417.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Janzen M. Virtual camera selection using a semiring constraint satisfaction approach. [Thesis]. University of Saskatchewan; 2012. Available from: http://hdl.handle.net/10388/ETD-2012-06-417

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Open Access Theses and Dissertations