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University of Bridgeport
1.
Al Essa, Ali.
Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection
.
Degree: 2018, University of Bridgeport
URL: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/3967 
► Early prediction of disease outbreaks and seasonal epidemics such as Influenza may reduce their impact on daily lives. Today, the web can be used for…
(more)
▼ Early prediction of disease outbreaks and seasonal epidemics such as Influenza may reduce their impact on daily lives. Today, the web can be used for surveillance of diseases.Search engines and Social Networking Sites can be used to track trends of different diseases more quickly than government agencies such as Center of Disease Control and Prevention(CDC). Today, Social Networking Sites (SNS) are widely used by diverse demographic populations. Thus, SNS data can be used effectively to track disease outbreaks and provide necessary warnings. Although the generated data of microblogging sites is valuable for real time analysis and outbreak predictions, the volume is huge. Therefore, one of the main challenges in analyzing this huge volume of data is to find the best approach for accurate analysis in an efficient time. Regardless of the analysis time, many studies show only the accuracy of applying different machine learning approaches. Current SNS-based flu detection and prediction frameworks apply conventional machine learning approaches that require lengthy training and testing, which is not the optimal solution for new outbreaks with new signs and symptoms. The aim of this study is to propose an efficient and accurate framework that uses SNS data to track disease outbreaks and provide early warnings, even for newest outbreaks accurately. The presented framework of outbreak prediction consists of three main modules: text classification, mapping, and linear regression for weekly flu rate predictions. The text classification module utilizes the features of sentiment analysis and predefined keyword occurrences. Various classifiers, including FastText and six conventional machine learning algorithms, are evaluated to identify the most efficient and accurate one for the proposed framework. The text classifiers have been trained and tested using a pre-labeled dataset of flu-related and unrelated Twitter postings. The selected text classifier is then used to classify over 8,400,000 tweet documents. The flu-related documents are then mapped ona weekly basis using a mapping module. Lastly, the mapped results are passed together with historical Center for Disease Control and Prevention (CDC) data to a linear regression module for weekly flu rate predictions. The evaluation of flu tweet classification shows that FastText together with the extracted features, has achieved accurate results with anF-measure value of 89.9% in addition to its efficiency. Therefore, FastText has been chosen to be the classification module to work together with the other modules in the proposed framework, including the linear regression module, for flu trend predictions. The prediction results are compared with the available recent data from CDC as the ground truth and show a strong correlation of 96.2%.
Subjects/Keywords: Influenza;
Linear regression
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APA (6th Edition):
Al Essa, A. (2018). Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection
. (Thesis). University of Bridgeport. Retrieved from https://scholarworks.bridgeport.edu/xmlui/handle/123456789/3967
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Al Essa, Ali. “Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection
.” 2018. Thesis, University of Bridgeport. Accessed April 11, 2021.
https://scholarworks.bridgeport.edu/xmlui/handle/123456789/3967.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Al Essa, Ali. “Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection
.” 2018. Web. 11 Apr 2021.
Vancouver:
Al Essa A. Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection
. [Internet] [Thesis]. University of Bridgeport; 2018. [cited 2021 Apr 11].
Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/3967.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Al Essa A. Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection
. [Thesis]. University of Bridgeport; 2018. Available from: https://scholarworks.bridgeport.edu/xmlui/handle/123456789/3967
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
2.
Feng, Yijia.
Robust Nonparametric Function Estimation with Serially Correlated Data
.
Degree: 2011, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/11391
► Nonparametric function estimation via local polynomial regression has been widely studied in the literature, especially in the past two decades. In practice, we confront two…
(more)
▼ Nonparametric function estimation via local polynomial
regression has been widely studied in the literature, especially in the past two decades. In practice, we confront two challenges. Firstly, the local least squares estimator may not be the best choice when errors are heavily tailed. Secondly, the data are correlated. In this thesis, we propose robust local
linear smoothing procedures to cope with nonparametric
regression and varying coefficient models with
the random error following a possible heavily tailed autoregressive (AR) process. Unlike classical local
linear technique, our method takes into account the specific error structure. This correlation information allows us to improve the estimation efficiency. Furthermore, by applying robust
regression techniques, the new
method is insensitive to outliers comparing with corresponding least squares approaches. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance. From our simulation studies, we find that the newly proposed procedures dramatically improve the accuracy over classical procedures under working-independence.
Advisors/Committee Members: Dr. Runze Li, Committee Chair/Co-Chair, Dr. Damla Senturk, Committee Member, Dr. Fuqing Zhang, Committee Member, Dr. Zhibiao Zhao, Committee Member.
Subjects/Keywords: autoregressive process; local linear regression; robust regression
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APA (6th Edition):
Feng, Y. (2011). Robust Nonparametric Function Estimation with Serially Correlated Data
. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/11391
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Feng, Yijia. “Robust Nonparametric Function Estimation with Serially Correlated Data
.” 2011. Thesis, Penn State University. Accessed April 11, 2021.
https://submit-etda.libraries.psu.edu/catalog/11391.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Feng, Yijia. “Robust Nonparametric Function Estimation with Serially Correlated Data
.” 2011. Web. 11 Apr 2021.
Vancouver:
Feng Y. Robust Nonparametric Function Estimation with Serially Correlated Data
. [Internet] [Thesis]. Penn State University; 2011. [cited 2021 Apr 11].
Available from: https://submit-etda.libraries.psu.edu/catalog/11391.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Feng Y. Robust Nonparametric Function Estimation with Serially Correlated Data
. [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/11391
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Arizona
3.
Clutter, Melissa Jean.
Designing Robust Measurement Networks Using Universal Multiple Linear Regression
.
Degree: 2019, University of Arizona
URL: http://hdl.handle.net/10150/633093
► Collecting hydrological data is essential for understanding system behavior and processes; without it, there is no basis for predictive modeling or risk assessment. Unfortunately, limited…
(more)
▼ Collecting hydrological data is essential for understanding system behavior and processes; without it, there is no basis for predictive modeling or risk assessment. Unfortunately, limited monitoring budgets often restrict measurement designs for field-based studies. Therefore, most field studies require some sort of data worth analysis to identify the most important data to collect with respect to the prediction(s) of interest. Data worth analyses can be either informal using methods such as trial-and-error, intuition, or rules of thumb, or formal using a quantitative metric to identify the most valuable data. My research focuses on a simple, computationally inexpensive formal data worth analysis which can be used in conjunction with more complex optimization approaches or when they are not warranted.
A key to network design is that the selection of sensor type, timing, and placement should be both informative and efficient. There are many possible individual sensor types and installation depths, and the key is to determine which sets of observations would be most effective prior to data collection. My research explores a combination of a method called universal Multiple
Linear Regression (uMLR) and Robust Decision Making (RDM) to identify these best observation sets. The uMLR method quantifies the explanatory power of all possible combinations of observations to the prediction(s) of interest and the RDM strategy further explores the impacts of user-defined uncertainties, including measurement error and parameter uncertainty, on these observation-set selections. Robust Decision Making is a concept developed by the Research and Development (RAND) Corporation and is designed to select a robust outcome under a range of uncertainty, at the risk of the selection being sub-optimal for any one specific uncertain outcome. Norgaard et al., (2014) previously used the uMLR approach to downsampling pre-existing data to identify a reduced set of parameters to describe the dispersibility of colloids. I offer an extension of the uMLR downsampling approach, based on model-simulated data, to consider optimizing data that have not yet been collected.
Advisors/Committee Members: Ferre, Ty (advisor), Meixner, Thomas (committeemember), Schaap, Marcel (committeemember).
Subjects/Keywords: design;
linear regression;
measurement;
optimization
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APA (6th Edition):
Clutter, M. J. (2019). Designing Robust Measurement Networks Using Universal Multiple Linear Regression
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/633093
Chicago Manual of Style (16th Edition):
Clutter, Melissa Jean. “Designing Robust Measurement Networks Using Universal Multiple Linear Regression
.” 2019. Doctoral Dissertation, University of Arizona. Accessed April 11, 2021.
http://hdl.handle.net/10150/633093.
MLA Handbook (7th Edition):
Clutter, Melissa Jean. “Designing Robust Measurement Networks Using Universal Multiple Linear Regression
.” 2019. Web. 11 Apr 2021.
Vancouver:
Clutter MJ. Designing Robust Measurement Networks Using Universal Multiple Linear Regression
. [Internet] [Doctoral dissertation]. University of Arizona; 2019. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10150/633093.
Council of Science Editors:
Clutter MJ. Designing Robust Measurement Networks Using Universal Multiple Linear Regression
. [Doctoral Dissertation]. University of Arizona; 2019. Available from: http://hdl.handle.net/10150/633093
University of Georgia
4.
Ganesan, Sivanesan.
Regression Leaf Forest.
Degree: 2014, University of Georgia
URL: http://hdl.handle.net/10724/27128
► There are a number of learning methods that provide solutions to classification and regression problems, including Linear Regression, Decision Trees, KNN, and SVMs. These methods…
(more)
▼ There are a number of learning methods that provide solutions to classification and regression problems, including Linear Regression, Decision Trees, KNN, and SVMs. These methods work well in many applications, but they are challenged for
real world problems that are noisy, non-linear or high dimensional. Furthermore, missing data (e.g., missing historical features of companies in stock data), is not managed well by current approaches. We present an implementation of a hybrid learning
system that combines an ensemble of decision trees (Random Forest) with of Linear Regression. Linear Regression (LR) is fast but not accurate because it assumes linearity, while Random Forests are not as fast as LR but have been shown to be accurate for
high dimensional and large data sets. By combining these approaches we address the weaknesses of each approach and exploit their strengths both in terms of real time performance and accuracy. In this thesis, we evaluate a hybrid Random Forest and Linear
Regression implementation called "Regression Leaf Forest", which is a forest of trees with regression leaves for supervised learning problems. The approach extends Random Forests by introducing Linear Regression learners at the leaf nodes of the trees
for predicting functions. Our empirical analysis on both real and artificial data shows that the proposed algorithm requires less computation time for both large and high-dimensional datasets while providing comparable or better accuracy when compared
to: Single Tree, a Single Linear Regression Tree, and Random Forest algorithms.
Subjects/Keywords: Random Forest; Linear Regression
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APA (6th Edition):
Ganesan, S. (2014). Regression Leaf Forest. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/27128
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Ganesan, Sivanesan. “Regression Leaf Forest.” 2014. Thesis, University of Georgia. Accessed April 11, 2021.
http://hdl.handle.net/10724/27128.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Ganesan, Sivanesan. “Regression Leaf Forest.” 2014. Web. 11 Apr 2021.
Vancouver:
Ganesan S. Regression Leaf Forest. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10724/27128.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Ganesan S. Regression Leaf Forest. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/27128
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Youngstown State University
5.
Jamison, Jonathan A.
Linear Regression Analysis of the Suspended Sediment Load in
Rivers and Streams Using Data of Similar Precipitation
Values.
Degree: MSin Environmental Science, Department of Physics, Astronomy, Geology and
Environmental Sciences, 2018, Youngstown State University
URL: http://rave.ohiolink.edu/etdc/view?acc_num=ysu154273822580279
► Sediment provides a method for transportation of a variety of other pollutants such as nutrients and potentially harmful bacteria. In addition, sediment can increase the…
(more)
▼ Sediment provides a method for transportation of a
variety of other pollutants such as nutrients and potentially
harmful bacteria. In addition, sediment can increase the cost of
water treatment processes and reduce storage volume of water
reservoirs. This study employs
linear regression to predict the
annual suspended sediment load, a dependent variable, as a function
of the annual river water discharge, an independent variable in
four United States Rivers. The available data (annual suspended
sediment load and annual river water discharge) for each river was
broken down into groups based upon similar precipitation values.
Each river was divided into two or three groups, with a total of
ten groups for the four rivers.
Linear regression was applied to
each group. Results of the precipitation approach were compared to
those of the traditional approach, the latter did not use any
precipitation data and thus there is no individual groupings. The
precipitation approach provided higher accuracy for the prediction
of the suspended sediment load when compared to the traditional
approach. The prediction accuracy is evident from the high
correlation coefficient values (between the suspended sediment and
river water discharge), and the low percent deviations (percent
difference between the observed and predicted suspended sediment).
Of the ten river groups, seven resulted in higher correlation
coefficients, and five gave lower percent deviations compared to
the traditional approach. The mean percent deviation ranged between
20 and 26% in seven groups, which is considered an indication of
high accuracy when suspended sediment is predicted by
linear
regression. All of the ten groups resulted in higher correlation
coefficient values greater or equal to 0.80, with four groups
exceeding 0.90.
Advisors/Committee Members: Amin, Isam (Committee Chair).
Subjects/Keywords: Environmental Science; Geomorphology; linear regression
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APA ·
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Manager
APA (6th Edition):
Jamison, J. A. (2018). Linear Regression Analysis of the Suspended Sediment Load in
Rivers and Streams Using Data of Similar Precipitation
Values. (Masters Thesis). Youngstown State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ysu154273822580279
Chicago Manual of Style (16th Edition):
Jamison, Jonathan A. “Linear Regression Analysis of the Suspended Sediment Load in
Rivers and Streams Using Data of Similar Precipitation
Values.” 2018. Masters Thesis, Youngstown State University. Accessed April 11, 2021.
http://rave.ohiolink.edu/etdc/view?acc_num=ysu154273822580279.
MLA Handbook (7th Edition):
Jamison, Jonathan A. “Linear Regression Analysis of the Suspended Sediment Load in
Rivers and Streams Using Data of Similar Precipitation
Values.” 2018. Web. 11 Apr 2021.
Vancouver:
Jamison JA. Linear Regression Analysis of the Suspended Sediment Load in
Rivers and Streams Using Data of Similar Precipitation
Values. [Internet] [Masters thesis]. Youngstown State University; 2018. [cited 2021 Apr 11].
Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ysu154273822580279.
Council of Science Editors:
Jamison JA. Linear Regression Analysis of the Suspended Sediment Load in
Rivers and Streams Using Data of Similar Precipitation
Values. [Masters Thesis]. Youngstown State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ysu154273822580279
6.
Peraça, Maria da Graça Teixeira.
Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação.
Degree: 2009, Universidade Federal do Rio Grande
URL: http://repositorio.furg.br/handle/1/3436
► Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós-Graduação em Engenharia Oceânica, Escola de Engenharia, 2009.
Nas engenharias, é fundamental estimar o tempo de…
(more)
▼ Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós-Graduação em Engenharia Oceânica, Escola de Engenharia, 2009.
Nas engenharias, é fundamental estimar o tempo de vida útil das estruturas construídas, o que neste trabalho significa o tempo que os íons cloretos levam para atingirem a armadura do concreto. Um dos coeficientes que influenciam na vida útil do concreto é o de difusão, sendo este diretamente influenciado pelo grau de saturação (GS) do concreto. Recentes estudos
levaram ao desenvolvimento de um método de medição do GS. Embora esse método seja
eficiente, ainda assim há um grande desperdício de tempo e dinheiro em utilizá-lo. O objetivo deste trabalho é reduzir estes custos calculando uma boa aproximação para o valor do GS com modelos matemáticos que estimem o seu valor através de variáveis ambientais que influenciam na sua variação. As variáveis analisadas nesta pesquisa, são: pressão atmosférica,temperatura do ar seco, temperatura máxima, temperatura mínima, taxa de evaporação interna (Pichê), taxa de precipitação, umidade relativa, insolação, visibilidade, nebulosidade e taxa de
evaporação externa. Todas foram analisadas e comparadas estatisticamente com medidas do
GS obtidas durante quatro anos de medições semanais, para diferentes famílias de concreto. Com essas análises, pode-se medir a relação entre estes dados verificando que os fatores mais influentes no GS são, temperatura máxima e umidade relativa. Após a verificação desse resultado, foram elaborados modelos estatísticos, para que, através dos dados ambientais, cedidos pelo banco de dados meteorológicos, se possam calcular, sem desperdício de tempo e dinheiro, as médias aproximadas do GS para cada estação sazonal da região sul do Brasil, garantindo assim uma melhor estimativa do tempo de vida útil em estruturas de concreto.
In engineering, it is fundamental to estimate the life-cycle of built structures, which in this study means the period of time required for chlorides to reach the concrete reinforcement. One of the coefficients that affect the life-cycle of concrete is the diffusion, which is directly influenced by the saturation degree (SD) of concrete. Recent studies have led to the development of a measurement method for the SD. Although this method is efficient, there is still waste of time and money when it is used. The objective of this study is to reduce costs by
calculating a good approximation for the SD value with mathematical models that predict its value through environmental variables that affect its variation. The variables analysed in the study are: atmospheric pressure, temperature of the dry air, maximum temperature, minimum temperature, internal evaporation rate (Pichê), precipitation rate, relative humidity, insolation, visibility, cloudiness and external evaporation rate. All of them were statistically analysed and compared with measurements of SD obtained during four years of weekly assessments for different families of concrete. By considering these analyses, the relationship among these data…
Advisors/Committee Members: Guimarães, André Tavares da Cunha.
Subjects/Keywords: Temperatura máxima; Regressão linear simples; Regressão linear múltipla; Maximum temperature; Linear regression; Multiple linear regression
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APA (6th Edition):
Peraça, M. d. G. T. (2009). Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação. (Masters Thesis). Universidade Federal do Rio Grande. Retrieved from http://repositorio.furg.br/handle/1/3436
Chicago Manual of Style (16th Edition):
Peraça, Maria da Graça Teixeira. “Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação.” 2009. Masters Thesis, Universidade Federal do Rio Grande. Accessed April 11, 2021.
http://repositorio.furg.br/handle/1/3436.
MLA Handbook (7th Edition):
Peraça, Maria da Graça Teixeira. “Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação.” 2009. Web. 11 Apr 2021.
Vancouver:
Peraça MdGT. Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação. [Internet] [Masters thesis]. Universidade Federal do Rio Grande; 2009. [cited 2021 Apr 11].
Available from: http://repositorio.furg.br/handle/1/3436.
Council of Science Editors:
Peraça MdGT. Modelos para estimativa do grau de saturação do concreto mediante variáveis ambientais que influenciam na sua variação. [Masters Thesis]. Universidade Federal do Rio Grande; 2009. Available from: http://repositorio.furg.br/handle/1/3436
Anna University
7.
Arulchinnappan S.
A study on fuzzy linear regression.
Degree: Mathematics, 2012, Anna University
URL: http://shodhganga.inflibnet.ac.in/handle/10603/17758
► The fuzzy set theory was first proposed by Zadeh in 1965. The fuzzy linear regression was proposed by Tanaka et al in 1982. Many different…
(more)
▼ The fuzzy set theory was first proposed by Zadeh in
1965. The fuzzy linear regression was proposed by Tanaka et al in
1982. Many different fuzzy regression approaches have been proposed
by different researchers. Since then this subject has drawn much
attention from more and more people concerned. There are two
approaches in fuzzy regression analysis, one is linear programming
based method and another one is fuzzy least square method. The
first method is based on minimizing fuzziness as an optimal
criterion and the second method is fuzzy least square method, which
is based on the notion of the distance between the predicted fuzzy
outputs and the observed fuzzy outputs and the goodness-of-fit. In
this work, we have used the Tanaka s possibilistic fuzzy linear
regression. We have considered a symmetric triangular fuzzy number
and have incorporated the concept of fuzzy linear system into the
fuzzy linear regression. The fuzzy coefficients involved in the
regression line are determined using normalized equations and the
fuzzy lines are determined. A numerical example is solved to
illustrate the efficiency of the proposed method. Next the fuzzy
linear regression equation is applied for the waste water treatment
to identify the chemical factors. Iv An algorithm for the newly
formulated fuzzy linear regression is developed. Data of oral
cancer patients have been collected and used in the algorithm to
identify the risk factors involved in oral cancer. The classical
correlation is converted into fuzzy correlation model. The fuzzy
lines of y on x and x on y are obtained. The collected oral cancer
data are utilized to identify the risk factors of oral cancer. The
data employed in fuzzy linear regression, algorithm and fuzzy
correlation methods have given reasonably good results in the
prediction of risk factors involved in the oral cancer. These
methods can serve as a powerful mathematical tool to predict the
risk factors involved in the chronic diseases in medical
domain.
References p. 75-89
Advisors/Committee Members: Viswanathan R.
Subjects/Keywords: Chronic diseases; Fuzzy set theory; Linear regression; Fuzzy linear regression
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APA ·
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Manager
APA (6th Edition):
S, A. (2012). A study on fuzzy linear regression. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/17758
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
S, Arulchinnappan. “A study on fuzzy linear regression.” 2012. Thesis, Anna University. Accessed April 11, 2021.
http://shodhganga.inflibnet.ac.in/handle/10603/17758.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
S, Arulchinnappan. “A study on fuzzy linear regression.” 2012. Web. 11 Apr 2021.
Vancouver:
S A. A study on fuzzy linear regression. [Internet] [Thesis]. Anna University; 2012. [cited 2021 Apr 11].
Available from: http://shodhganga.inflibnet.ac.in/handle/10603/17758.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
S A. A study on fuzzy linear regression. [Thesis]. Anna University; 2012. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/17758
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Georgia State University
8.
Chernishkin, Amanda E.
Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods.
Degree: MPH, Public Health, 2020, Georgia State University
URL: https://scholarworks.gsu.edu/iph_theses/714
► This study investigates three alternative machine learning methods to explore influential predictors of type 2 diabetes. It compares ridge, lasso, and elastic net regression…
(more)
▼ This study investigates three alternative machine learning methods to explore influential predictors of type 2 diabetes. It compares ridge, lasso, and elastic net
regression to
linear regression, and focuses on 12 outcome variables that include age, sex, race, income, education level, body mass index, waist circumference, arm circumference, hip circumference, family history, smoking status, sleep duration, high blood pressure, and high-density lipoprotein. Ridge, lasso and elastic net
regression do not outperform
linear regression but do assist in choosing a simpler model which could be important for improving future modeling.
Advisors/Committee Members: David Ashley, Dora Ilyasova, Ruiyan Luo.
Subjects/Keywords: machine learning; lasso regression; ridge regression; elastic net regression; type 2 diabetes; linear regression
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APA (6th Edition):
Chernishkin, A. E. (2020). Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/iph_theses/714
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Chernishkin, Amanda E. “Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods.” 2020. Thesis, Georgia State University. Accessed April 11, 2021.
https://scholarworks.gsu.edu/iph_theses/714.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Chernishkin, Amanda E. “Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods.” 2020. Web. 11 Apr 2021.
Vancouver:
Chernishkin AE. Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods. [Internet] [Thesis]. Georgia State University; 2020. [cited 2021 Apr 11].
Available from: https://scholarworks.gsu.edu/iph_theses/714.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Chernishkin AE. Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods. [Thesis]. Georgia State University; 2020. Available from: https://scholarworks.gsu.edu/iph_theses/714
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas A&M University
9.
Van Huyck, Carl Phillips.
A Matrix Based Approach for Color Transformations in Reflections.
Degree: MS, Visualization, 2018, Texas A&M University
URL: http://hdl.handle.net/1969.1/173569
► In this thesis, I demonstrate the feasibility of linear regression with 4 × 4 matrices to perform color transformations, specifically looking at the case of…
(more)
▼ In this thesis, I demonstrate the feasibility of
linear regression with 4 × 4 matrices to perform color transformations, specifically looking at the case of color transformations in reflections. I compare and analyze the power and performance
linear regression models based on 3 × 3 and 4 × 4 matrices. I conclude that using 4 × 4 matrices in
linear regression is more advantageous in power and performance over using 3 × 3 matrices in
linear regressions, as 4 × 4 matrices allow for categorically more transformations by including the possibility of translation. This provides more general affine transformations to a color space, rather than being restricted to passing through the origin. I examine the benefits of allowing for negative elements in color transformation matrices. I also touch on the possible differences in application between filled 4 × 4 matrices and diagonal 4 × 4 matrices, and discuss the limitations inherent to
linear regression used in any type of matrix operations.
Advisors/Committee Members: Akleman, Ergun (advisor), Shell, Dylan (committee member), Davison, Richard (committee member), Furuta, Richard (committee member).
Subjects/Keywords: Reflections; Computer Graphics; Color; Matrices; Linear Regression
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APA (6th Edition):
Van Huyck, C. P. (2018). A Matrix Based Approach for Color Transformations in Reflections. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173569
Chicago Manual of Style (16th Edition):
Van Huyck, Carl Phillips. “A Matrix Based Approach for Color Transformations in Reflections.” 2018. Masters Thesis, Texas A&M University. Accessed April 11, 2021.
http://hdl.handle.net/1969.1/173569.
MLA Handbook (7th Edition):
Van Huyck, Carl Phillips. “A Matrix Based Approach for Color Transformations in Reflections.” 2018. Web. 11 Apr 2021.
Vancouver:
Van Huyck CP. A Matrix Based Approach for Color Transformations in Reflections. [Internet] [Masters thesis]. Texas A&M University; 2018. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/1969.1/173569.
Council of Science Editors:
Van Huyck CP. A Matrix Based Approach for Color Transformations in Reflections. [Masters Thesis]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173569
University of Waikato
10.
Liu, Liang.
Linear Genetic Programming with Experience
.
Degree: 2015, University of Waikato
URL: http://hdl.handle.net/10289/9762
► A novel method of using Machine Learning (ML) algorithms to improve the performance of Linear Genetic Programming (LGP) is studied. In this study, structures used…
(more)
▼ A novel method of using Machine Learning (ML) algorithms to improve the performance of
Linear Genetic Programming (LGP) is studied. In this study, structures used to organize the trained ML models are called Experience Models (EM). They are used for different mutate actions of the mutation operator in LGP. The purpose of using EM is to regulate the random search performed by the mutation operator. The aim of using EMs is to let the suitable candidates have higher chances to be selected.
In this study, two sources of knowledge are used to create the training sets that are used to train ML models. The first source is the pre-existing knowledge of symbolic
regression. This knowledge reflects the effect of adding one math function segment to another math function segment. The second source is the knowledge generated during the evolution of LGP. This knowledge reflects the effect of using different gene components at different chromosome indexes on the overall fitness. Based on these two sources of knowledge, two types of EM are designed. They are Static Model (SM) and Dynamic Model (DM). The SM uses ML models trained with the first knowledge source. A SM tries to achieve the aim of using an EM by reducing the size of the candidate sets used by the increase action of the mutation operator. The DM uses ML models trained with the second knowledge source. A DM tries to achieve the aim of using an EM by creating distributions of gene component types, which can reflect the information in the second knowledge source, for change action of the mutation operator. In this study, SM is used only for increase action in the mutation operator; DM is used only for change action in the mutation operator.
From the experiment results, if compared with a LGP, when a LGP using a SM, it tends to need fewer generations to have a hit, at the same time achieving similar mean best fitness. In contrary, when used with a DM, a LGP do not show performance improvements.
Advisors/Committee Members: Mayo, Michael (advisor).
Subjects/Keywords: Linear Genetic Programming;
Machine Learning;
Symbolic Regression
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APA ·
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Manager
APA (6th Edition):
Liu, L. (2015). Linear Genetic Programming with Experience
. (Masters Thesis). University of Waikato. Retrieved from http://hdl.handle.net/10289/9762
Chicago Manual of Style (16th Edition):
Liu, Liang. “Linear Genetic Programming with Experience
.” 2015. Masters Thesis, University of Waikato. Accessed April 11, 2021.
http://hdl.handle.net/10289/9762.
MLA Handbook (7th Edition):
Liu, Liang. “Linear Genetic Programming with Experience
.” 2015. Web. 11 Apr 2021.
Vancouver:
Liu L. Linear Genetic Programming with Experience
. [Internet] [Masters thesis]. University of Waikato; 2015. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10289/9762.
Council of Science Editors:
Liu L. Linear Genetic Programming with Experience
. [Masters Thesis]. University of Waikato; 2015. Available from: http://hdl.handle.net/10289/9762
University of Vermont
11.
Berger, Alex.
Using Crowdsourcing to Discover Correlational Relationships.
Degree: Computer Science, 2014, University of Vermont
URL: https://scholarworks.uvm.edu/hcoltheses/33
► Obtaining hypotheses for scientific experiments can be an exceptionally challenging and time-consuming task. Even with specialized knowledge, researchers frequently overlook important variables that may…
(more)
▼ Obtaining hypotheses for scientific experiments can be an exceptionally challenging and time-consuming task. Even with specialized knowledge, researchers frequently overlook important variables that may be strongly correlated with their outcome of interest. This experiment explores the use of crowdsourcing as a potentially more efficient way of gathering hypotheses. Testing the effectiveness of crowdsourcing involved the creation of a website that would enable users to build an online survey consisting of questions that may be predictive of a specified response variable. Contributions were obtained from members of online communities interested in subjects related to the area of research being studied. Allowing users to answer preexisting questions and add new questions to the survey resulted in a substantial amount of data on hundreds of potentially related variables. This data could then be used to determine which of the proposed factors are most correlated with the outcome of interest. Strongly correlated variables could later be studied in more detail in future experiments. Though this experiment specifically aims to identify factors that may be predictive of someone’s personal savings, this method of crowdsourcing can be replicated by researchers in any field of study. Using crowdsourcing to gather preliminary data has the potential to improve the efficiency of academic research and increase the rate of scientific discoveries.
Advisors/Committee Members: Josh Bongard.
Subjects/Keywords: crowdsourcing; computer science; machine learning; linear regression
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APA (6th Edition):
Berger, A. (2014). Using Crowdsourcing to Discover Correlational Relationships. (Thesis). University of Vermont. Retrieved from https://scholarworks.uvm.edu/hcoltheses/33
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Berger, Alex. “Using Crowdsourcing to Discover Correlational Relationships.” 2014. Thesis, University of Vermont. Accessed April 11, 2021.
https://scholarworks.uvm.edu/hcoltheses/33.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Berger, Alex. “Using Crowdsourcing to Discover Correlational Relationships.” 2014. Web. 11 Apr 2021.
Vancouver:
Berger A. Using Crowdsourcing to Discover Correlational Relationships. [Internet] [Thesis]. University of Vermont; 2014. [cited 2021 Apr 11].
Available from: https://scholarworks.uvm.edu/hcoltheses/33.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Berger A. Using Crowdsourcing to Discover Correlational Relationships. [Thesis]. University of Vermont; 2014. Available from: https://scholarworks.uvm.edu/hcoltheses/33
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Vermont
12.
Eberling, Jennifer.
Predictive Modeling of the Outcomes of University of Vermont Women’s Basketball Games.
Degree: Mathematics and Statistics, 2020, University of Vermont
URL: https://scholarworks.uvm.edu/hcoltheses/342
► Every year the University of Vermont Women’s Basketball team plays 16 games for the America East Conference. Data was collected over two seasons to…
(more)
▼ Every year the University of Vermont Women’s Basketball team plays 16 games for the America East Conference. Data was collected over two seasons to create a prediction model for the score of a game. Zone percentages were collected in addition to typical basketball statistics. Variables in the model were first picked based on linearity, then finalized using Akaike’s Information Criterion. The resulting
linear model is evaluated in R. This model is intended to help the UVM Women’s Basketball Team understand the most important factors of their games.
Advisors/Committee Members: Bernard Cole.
Subjects/Keywords: statistics; basketball; score; regression; predict; linear
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APA (6th Edition):
Eberling, J. (2020). Predictive Modeling of the Outcomes of University of Vermont Women’s Basketball Games. (Thesis). University of Vermont. Retrieved from https://scholarworks.uvm.edu/hcoltheses/342
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Eberling, Jennifer. “Predictive Modeling of the Outcomes of University of Vermont Women’s Basketball Games.” 2020. Thesis, University of Vermont. Accessed April 11, 2021.
https://scholarworks.uvm.edu/hcoltheses/342.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Eberling, Jennifer. “Predictive Modeling of the Outcomes of University of Vermont Women’s Basketball Games.” 2020. Web. 11 Apr 2021.
Vancouver:
Eberling J. Predictive Modeling of the Outcomes of University of Vermont Women’s Basketball Games. [Internet] [Thesis]. University of Vermont; 2020. [cited 2021 Apr 11].
Available from: https://scholarworks.uvm.edu/hcoltheses/342.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Eberling J. Predictive Modeling of the Outcomes of University of Vermont Women’s Basketball Games. [Thesis]. University of Vermont; 2020. Available from: https://scholarworks.uvm.edu/hcoltheses/342
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Baylor University
13.
Guo, Yuanyuan, 1984-.
Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression.
Degree: PhD, Baylor University. Dept. of Statistical Sciences., 2015, Baylor University
URL: http://hdl.handle.net/2104/9557
► Conventional Phase II clinical trial designs usually employ a logistic regression model to analyze the efficacy of a new drug and, therefore, assumes monotone dose-response…
(more)
▼ Conventional Phase II clinical trial designs usually employ a logistic
regression model to analyze the efficacy of a new drug and, therefore, assumes monotone dose-response relationship. Also, the logistic
regression model requires the response to be categorical and, thus, it is not applicable for continuous data. The traditional design in Phase II determines if a new drug will be further tested in Phase III based on only drug efficacy and allocates an equal number of patients to each dosage, ignoring dose efficacy. Because of the limitations of conventional clinical trial designs, new adaptive designs have been proposed by researchers to improve the flexibility and adaptability of conventional designs. In Chapter Two we propose an adaptive Bayesian design that uses a bivariate normal dynamic
linear model for a Phase II clinical trial, and we compare its performance to a Bayesian fixed or non-adaptive design. The proposed Bayesian adaptive design can be utilized for continuous data and can model various dose-response relationships. We remark that for many dose-response relationships, our proposed adaptive Bayesian design can use fewer patients to obtain a correct decision concerning a drug's efficacy than the Bayesian fixed design. Missing data arises in almost all research; that is, part of the data are missing for a
subject. A data analyst must decide how to cope with the missing data from among the numerous imputation methods that can be used. However, one might not know which imputation method is the best. The objective of this study is to evaluate the efficacy of five imputation methods. In Chapter Four, we have compared the performance of complete-data-only, single-mean imputation, conditional-mean imputation, multiple imputation by chained equations and hotdeck imputation methods for prediction of a logistic
regression model, for the missing-completely-at-random and missing-at-random mechanisms. These five imputation methods yield different results for small sample sizes, and the difference decreases with an increasing sample size. Surprisingly, a single-mean imputation method performs as well as the multiple imputation methods compared here.
Advisors/Committee Members: Young, Dean M. (advisor).
Subjects/Keywords: Clinical trial. Dynamic linear model. Logistic regression.
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APA (6th Edition):
Guo, Yuanyuan, 1. (2015). Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. (Doctoral Dissertation). Baylor University. Retrieved from http://hdl.handle.net/2104/9557
Chicago Manual of Style (16th Edition):
Guo, Yuanyuan, 1984-. “Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression.” 2015. Doctoral Dissertation, Baylor University. Accessed April 11, 2021.
http://hdl.handle.net/2104/9557.
MLA Handbook (7th Edition):
Guo, Yuanyuan, 1984-. “Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression.” 2015. Web. 11 Apr 2021.
Vancouver:
Guo, Yuanyuan 1. Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. [Internet] [Doctoral dissertation]. Baylor University; 2015. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/2104/9557.
Council of Science Editors:
Guo, Yuanyuan 1. Topics in Bayesian adaptive clinical trial design using dynamic linear models and missing data imputation in logistic regression. [Doctoral Dissertation]. Baylor University; 2015. Available from: http://hdl.handle.net/2104/9557
14.
Mahmood, Arshad.
Rainfall prediction in Australia : Clusterwise linear regression approach.
Degree: PhD, 2017, Federation University Australia
URL: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/159251
;
https://library.federation.edu.au/record=b2722196
► Accurate rainfall prediction is a challenging task because of the complex physical processes involved. This complexity is compounded in Australia as the climate can be…
(more)
▼ Accurate rainfall prediction is a challenging task because of the complex physical processes involved. This complexity is compounded in Australia as the climate can be highly variable. Accurate rainfall prediction is immensely benecial for making informed policy, planning and management decisions, and can assist with the most sustainable operation of water resource systems. Short-term prediction of rainfall is provided by meteorological services; however, the intermediate to long-term prediction of rainfall remains challenging and contains much uncertainty. Many prediction approaches have been proposed in the literature, including statistical and computational intelligence approaches. However, finding a method to model the complex physical process of rainfall, especially in Australia where the climate is highly variable, is still a major challenge. The aims of this study are to: (a) develop an optimization based clusterwise linear regression method, (b) develop new prediction methods based on clusterwise linear regression, (c) assess the influence of geographic regions on the performance of prediction models in predicting monthly and weekly rainfall in Australia, (d) determine the combined influence of meteorological variables on rainfall prediction in Australia, and (e) carry out a comparative analysis of new and existing prediction techniques using Australian rainfall data. In this study, rainfall data with five input meteorological variables from 24 geographically diverse weather stations in Australia, over the period January 1970 to December 2014, have been taken from the Scientific Information for Land Owners (SILO). We also consider the climate zones when selecting weather stations, because Australia experiences a variety of climates due to its size. The data was divided into training and testing periods for evaluation purposes. In this study, optimization based clusterwise linear regression is modified and new prediction methods are developed for rainfall prediction. The proposed method is applied to predict monthly and weekly rainfall. The prediction performance of the clusterwise linear regression method was evaluated by comparing observed and predicted rainfall values using the performance measures: root mean squared error, the mean absolute error, the mean absolute scaled error and the Nash-Sutclie coefficient of efficiency. The proposed method is also compared with the clusterwise linear regression based on the maximum likelihood estimation, linear support vector machines for regression, support vector machines for regression with radial basis kernel function, multiple linear regression, artificial neural networks with and without hidden layer and k-nearest neighbours methods using computational results. Initially, to determine the appropriate input variables to be used in the investigation, we assessed all combinations of meteorological variables. The results confirm that single meteorological variables alone are unable to predict rainfall accurately. The prediction performance of all selected models was…
Subjects/Keywords: Accurate rainfall prediction; Clusterwise linear regression; Australia
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Export
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Manager
APA (6th Edition):
Mahmood, A. (2017). Rainfall prediction in Australia : Clusterwise linear regression approach. (Doctoral Dissertation). Federation University Australia. Retrieved from http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/159251 ; https://library.federation.edu.au/record=b2722196
Chicago Manual of Style (16th Edition):
Mahmood, Arshad. “Rainfall prediction in Australia : Clusterwise linear regression approach.” 2017. Doctoral Dissertation, Federation University Australia. Accessed April 11, 2021.
http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/159251 ; https://library.federation.edu.au/record=b2722196.
MLA Handbook (7th Edition):
Mahmood, Arshad. “Rainfall prediction in Australia : Clusterwise linear regression approach.” 2017. Web. 11 Apr 2021.
Vancouver:
Mahmood A. Rainfall prediction in Australia : Clusterwise linear regression approach. [Internet] [Doctoral dissertation]. Federation University Australia; 2017. [cited 2021 Apr 11].
Available from: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/159251 ; https://library.federation.edu.au/record=b2722196.
Council of Science Editors:
Mahmood A. Rainfall prediction in Australia : Clusterwise linear regression approach. [Doctoral Dissertation]. Federation University Australia; 2017. Available from: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/159251 ; https://library.federation.edu.au/record=b2722196
Michigan Technological University
15.
Feng, Lilia.
Bayesian Hypothesis Testing in Linear Regression Models.
Degree: PhD, Department of Mathematical Sciences, 2019, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/928
► This dissertation consists of five chapters with three distinct but related research projects. In Chapter 1, we introduce some necessary definitions related to the…
(more)
▼ This dissertation consists of five chapters with three distinct but related research projects.
In Chapter 1, we introduce some necessary definitions related to the research work.
In Chapter 2, we develop Bayes factor based testing procedures for a general
linear hypothesis of the
regression coefficients in the context of the normal
linear models. We propose two calibration schemes to deal with asymmetry in information of Bayes factor: (i) by controlling Type I error probability of the Bayes factor and (ii) by balancing Type I and Type II error probabilities of the Bayes factor. We evaluate the finite sample performance of the proposed Bayes factors via simulation studies and a real-data application. Experimental results have shown than the proposed Bayes factors perform well in testing the general
linear hypothesis of the
regression coefficient.
In Chapter 3, we consider Bayesian quantile analysis for testing constrained hypotheses in
linear models, in which the quantiles the parameters satisfy a simple order restriction. We develop a Bayesian hierarchical model based on the specification the asymmetric Laplace distribution for the error component. We propose a non-iterative sampling algorithm in the Expectation-Maximization (EM) structure to generate independently and identically distributed posterior samples from their posterior distributions of the parameters. Then we adopt the Savage-Dickey density ratios to conduct the multiple comparison with simply order constraints. Simulation studies were conducted to compare the finite sample performance of the proposed non-iterative sampling algorithm with the Gibbs sampling algorithm.
In Chapter 4, we consider objective Bayesian analysis for the concordance correlation coefficient (CCC), which is one of the most commonly used metrics to assess agreement of different methods in many practical applications. We develop an objective Bayesian framework for estimating the CCC based a combined use of the multivariate student's t-distribution with noninformative Independence Jeffreys prior for the unknown parameters. Extensive simulation studies are conducted to compare the performance of the proposed Bayesian estimates with the ones under the subjective priors in the literature.
In Chapter 5, we discuss some ongoing projects related to our research work mentioned above and some interesting problems for future work.
Advisors/Committee Members: Min Wang.
Subjects/Keywords: Bayesian Statistics; Hypothesis Testing; Linear Regression Models
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Export
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Manager
APA (6th Edition):
Feng, L. (2019). Bayesian Hypothesis Testing in Linear Regression Models. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/928
Chicago Manual of Style (16th Edition):
Feng, Lilia. “Bayesian Hypothesis Testing in Linear Regression Models.” 2019. Doctoral Dissertation, Michigan Technological University. Accessed April 11, 2021.
https://digitalcommons.mtu.edu/etdr/928.
MLA Handbook (7th Edition):
Feng, Lilia. “Bayesian Hypothesis Testing in Linear Regression Models.” 2019. Web. 11 Apr 2021.
Vancouver:
Feng L. Bayesian Hypothesis Testing in Linear Regression Models. [Internet] [Doctoral dissertation]. Michigan Technological University; 2019. [cited 2021 Apr 11].
Available from: https://digitalcommons.mtu.edu/etdr/928.
Council of Science Editors:
Feng L. Bayesian Hypothesis Testing in Linear Regression Models. [Doctoral Dissertation]. Michigan Technological University; 2019. Available from: https://digitalcommons.mtu.edu/etdr/928
16.
Hamal, Tamanna.
Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students.
Degree: MS, Mathematics, 2017, Texas Woman's University
URL: http://hdl.handle.net/11274/9356
► The purpose of the study is to compare the Discriminant Analysis and Linear Regression Analysis to predict the correlation between alcohol consumption by high school…
(more)
▼ The purpose of the study is to compare the Discriminant Analysis and
Linear Regression Analysis to predict the correlation between alcohol consumption by high school students and their social attributes and grades. Discriminant Analysis, developed by R. A. Fisher in 1936, is a statistical technique used to determine which variables discriminate between two or more mutually exclusive naturally occurring groups.
Linear Regression Analysis is the most widely used statistical technique where straight lines are fitted to patterns of data. In this model, the dependent variable, the variable of interest, is predicted from independent variables using a
linear equation. Even though the earliest form of
linear regression was the Method of Least Squares, which was published by Legendre in 1805, and by Gauss in 1809, the term
regression was pioneered by Sir Francis Galton.
Regression analysis is the process of finding out the relationship between one or more dependent variables and the independent variables.
Advisors/Committee Members: Marshall, David (Committee Chair), Falley, Brandi (committee member), Edwards, Don (committee member).
Subjects/Keywords: Pure sciences; Analysis; Discriminant; Linear regression; SPSS
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Manager
APA (6th Edition):
Hamal, T. (2017). Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students. (Masters Thesis). Texas Woman's University. Retrieved from http://hdl.handle.net/11274/9356
Chicago Manual of Style (16th Edition):
Hamal, Tamanna. “Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students.” 2017. Masters Thesis, Texas Woman's University. Accessed April 11, 2021.
http://hdl.handle.net/11274/9356.
MLA Handbook (7th Edition):
Hamal, Tamanna. “Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students.” 2017. Web. 11 Apr 2021.
Vancouver:
Hamal T. Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students. [Internet] [Masters thesis]. Texas Woman's University; 2017. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/11274/9356.
Council of Science Editors:
Hamal T. Comparing discriminant analysis and linear regression analysis to predict the alcohol consumption by high school students. [Masters Thesis]. Texas Woman's University; 2017. Available from: http://hdl.handle.net/11274/9356
University of Arizona
17.
Kaye, Justin.
Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
.
Degree: 2019, University of Arizona
URL: http://hdl.handle.net/10150/633086
► Background: Warfarin remains one of the most widely prescribed anticoagulants but is also a leading cause of adverse drug reactions. Genotype-guided warfarin dosing algorithms enable…
(more)
▼ Background: Warfarin remains one of the most widely prescribed anticoagulants but is also a leading cause of adverse drug reactions. Genotype-guided warfarin dosing algorithms enable accurate dose estimation, potentially leading to improved safety and efficacy. However, genotype-guided dosing algorithms were developed primarily in populations of European descent and limited data are available regarding single nucleotide polymorphisms (SNPs) that significantly influence warfarin dose in Hispanic populations.
Research Aim: The objective of this study was to determine whether clinical factors and SNPs previously associated with stable warfarin dose variability in populations of European and Hispanic descent accurately predicted warfarin stable dose in a Hispanic population.
Study Design: Self-reported Hispanic and Latino patients on stable warfarin dose (defined as the same dose for at least two clinic visits separated by at least two weeks) were recruited.
Methods: Candidate SNPs, including CYP2C9*2/*3, VKORC1-1639G>A, CYP4F2*3, and NQO1*2, were genotyped and clinical data were collected using a survey and the electronic medical record. Stepwise
linear regression was performed to determine variables that significantly predicted square root of weekly warfarin dose.
Results: A total of 76 patients of primarily Mexican American ancestry participated. All SNPs were within Hardy-Weinberg Equilibrium. The final stepwise
regression model incorporated six variables, which explained 71% of the variability in warfarin weekly dose requirements. Significant predictors included weight (R2=0.287, p<0.0001), age (R2=0.143, p<0.0001), amiodarone use (R2=0.067, p=0.0005), and prior stroke (R2=0.025, p=0.02). Significant SNPs included VKORC1-1639A (R2=0.152, p<0.0001), and CYP2C9*2/*3 (R2=0.032, p=0.02). CYP4F2*3 and NQO1*2 did not significantly impact warfarin dose requirements despite previously published associations in Hispanic populations.
Conclusion: These findings suggest that clinical and genetic predictors of warfarin weekly dose requirements are similar among populations of European descent and Hispanic populations with Mexican American ancestry. These results require replication and validation in independent cohorts with similar ethnicity, but advance our understanding of influences on warfarin dose variability among different race/ethnic groups.
Advisors/Committee Members: Karnes, Jason H (advisor), Laukaitis, Christina M. (committeemember), Darnell, Diana K. (committeemember).
Subjects/Keywords: Hispanic;
Latino;
linear regression;
Pharmacogenomics;
SNP;
Warfarin
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APA (6th Edition):
Kaye, J. (2019). Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
. (Masters Thesis). University of Arizona. Retrieved from http://hdl.handle.net/10150/633086
Chicago Manual of Style (16th Edition):
Kaye, Justin. “Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
.” 2019. Masters Thesis, University of Arizona. Accessed April 11, 2021.
http://hdl.handle.net/10150/633086.
MLA Handbook (7th Edition):
Kaye, Justin. “Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
.” 2019. Web. 11 Apr 2021.
Vancouver:
Kaye J. Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
. [Internet] [Masters thesis]. University of Arizona; 2019. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10150/633086.
Council of Science Editors:
Kaye J. Warfarin Pharmacogenomics in a Hispanic Population: A Candidate SNP Study
. [Masters Thesis]. University of Arizona; 2019. Available from: http://hdl.handle.net/10150/633086
Kansas State University
18.
Cao, Chendi.
Linear
regression with Laplace measurement error.
Degree: MS, Statistics, 2016, Kansas State University
URL: http://hdl.handle.net/2097/32719
► In this report, an improved estimation procedure for the regression parameter in simple linear regression models with the Laplace measurement error is proposed. The estimation…
(more)
▼ In this report, an improved estimation procedure for
the
regression parameter in simple
linear regression models with
the Laplace measurement error is proposed. The estimation procedure
is made feasible by a Tweedie type equality established for E(X|Z),
where Z = X + U, X and U are independent, and U follows a Laplace
distribution. When the density function of X is unknown, a kernel
estimator for E(X|Z) is constructed in the estimation procedure. A
leave-one-out cross validation bandwidth selection method is
designed. The finite sample performance of the proposed estimation
procedure is evaluated by simulation studies. Comparison study is
also conducted to show the superiority of the proposed estimation
procedure over some existing estimation methods.
Advisors/Committee Members: Weixing Song.
Subjects/Keywords: Measurement
error; Laplace
distribution; Linear
regression
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Cao, C. (2016). Linear
regression with Laplace measurement error. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/32719
Chicago Manual of Style (16th Edition):
Cao, Chendi. “Linear
regression with Laplace measurement error.” 2016. Masters Thesis, Kansas State University. Accessed April 11, 2021.
http://hdl.handle.net/2097/32719.
MLA Handbook (7th Edition):
Cao, Chendi. “Linear
regression with Laplace measurement error.” 2016. Web. 11 Apr 2021.
Vancouver:
Cao C. Linear
regression with Laplace measurement error. [Internet] [Masters thesis]. Kansas State University; 2016. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/2097/32719.
Council of Science Editors:
Cao C. Linear
regression with Laplace measurement error. [Masters Thesis]. Kansas State University; 2016. Available from: http://hdl.handle.net/2097/32719
California State University – Sacramento
19.
Manjiyani, Zainiya.
Public health awareness system using blockchain.
Degree: MS, Computer Science, 2020, California State University – Sacramento
URL: http://hdl.handle.net/10211.3/215207
► Technological advancement in the medical field introduced many advanced appliances that changed the way we live. People became more conscious about their health using fitness…
(more)
▼ Technological advancement in the medical field introduced many advanced appliances that changed the way we live. People became more conscious about their health using fitness tracking applications and wearable devices. Despite the progress made in this direction and solutions being cost effective, many people are not aware about preventive measures for widespread diseases that are currently spreading in their neighborhood. As per the survey conducted in India during 2015 [1], due to lack of awareness, 33761 confirmed Swine flu cases and 2035 deaths were reported. Out of 33761 cases, 6495 swine flu cases and 428 deaths were observed within the state of Gujarat. The goal of this project is to create awareness among people regarding preventive measures to fight against contagious diseases that are widespread in their neighborhood.
Public health awareness system using blockchain is an alert system which is built with the combination of Blockchain and Artificial Intelligence. Patient records are vulnerable and could be manipulated by unauthorized user. Hence an advanced technology like blockchain facilitates high security, decentralization, and tamper-proof, is used for transmission of patient records [2]. Another major aspect of the system is to predict the number of cases for the disease in a particular area. This is done in two steps; first a cluster of neighboring zip codes is created, and then prediction is made using
regression model considering past 7 days of data. The code then generates list of alerts if the probability of disease exceeds a predetermined threshold.
Advisors/Committee Members: Ouyang, Jinsong.
Subjects/Keywords: Health alert; Ethereum; Linear regression; Web3
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Manjiyani, Z. (2020). Public health awareness system using blockchain. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/215207
Chicago Manual of Style (16th Edition):
Manjiyani, Zainiya. “Public health awareness system using blockchain.” 2020. Masters Thesis, California State University – Sacramento. Accessed April 11, 2021.
http://hdl.handle.net/10211.3/215207.
MLA Handbook (7th Edition):
Manjiyani, Zainiya. “Public health awareness system using blockchain.” 2020. Web. 11 Apr 2021.
Vancouver:
Manjiyani Z. Public health awareness system using blockchain. [Internet] [Masters thesis]. California State University – Sacramento; 2020. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10211.3/215207.
Council of Science Editors:
Manjiyani Z. Public health awareness system using blockchain. [Masters Thesis]. California State University – Sacramento; 2020. Available from: http://hdl.handle.net/10211.3/215207
Georgia State University
20.
Rudresh, Vinay.
Associations between Depression and Blood Pressure among United States Adults: A Bayesian vs. Frequentist Approach.
Degree: MPH, Public Health, 2020, Georgia State University
URL: https://scholarworks.gsu.edu/iph_theses/707
► High blood pressure can lead to life threatening incidents such as a heart attack or stroke. The direct costs of high blood pressure are…
(more)
▼ High blood pressure can lead to life threatening incidents such as a heart attack or stroke. The direct costs of high blood pressure are expected to rise to 154 billion dollars annually by 2035. Depression is one of the most prevalent mental illnesses in the United States with an estimated 35% of those who experienced major depressive episodes not receiving treatment. The research question this study aims to answer is if there is an association between depression and blood pressure. This study also aims to see if results are comparable between models using frequentist statistics and Bayesian models using weakly informative priors and informative priors. To assess the association,
linear regressions of crude and adjusted associations between depression and systolic/diastolic blood pressure were run. The same models were run using Bayesian weakly informative priors and informative priors. Only the model implementing Bayesian informative priors found an association between depression and systolic blood pressure with a mean of 0.119 (95% Confidence Interval: 0.024, 0.216). However, the association was unadjusted. The association between depression and systolic blood pressure is statistically significant, but it lacks clinical significance.
Advisors/Committee Members: Ruiyan Luo, Ph.D., Sheryl Strasser, Ph.D..
Subjects/Keywords: Depression; Blood pressure; Hypertension; Bayesian; linear regression
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APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Rudresh, V. (2020). Associations between Depression and Blood Pressure among United States Adults: A Bayesian vs. Frequentist Approach. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/iph_theses/707
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Rudresh, Vinay. “Associations between Depression and Blood Pressure among United States Adults: A Bayesian vs. Frequentist Approach.” 2020. Thesis, Georgia State University. Accessed April 11, 2021.
https://scholarworks.gsu.edu/iph_theses/707.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Rudresh, Vinay. “Associations between Depression and Blood Pressure among United States Adults: A Bayesian vs. Frequentist Approach.” 2020. Web. 11 Apr 2021.
Vancouver:
Rudresh V. Associations between Depression and Blood Pressure among United States Adults: A Bayesian vs. Frequentist Approach. [Internet] [Thesis]. Georgia State University; 2020. [cited 2021 Apr 11].
Available from: https://scholarworks.gsu.edu/iph_theses/707.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Rudresh V. Associations between Depression and Blood Pressure among United States Adults: A Bayesian vs. Frequentist Approach. [Thesis]. Georgia State University; 2020. Available from: https://scholarworks.gsu.edu/iph_theses/707
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Delft University of Technology
21.
Wang, Xinyi (author).
Forecasting tourist counts with historical counts and external features.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:858b0720-5ee5-49d1-bef3-c3a031717573
► This research explored two types of models, ARIMA and multiple linear regression, for forecasting tourist counts in 7 locations around Amsterdam red light district, for…
(more)
▼ This research explored two types of models, ARIMA and multiple linear regression, for forecasting tourist counts in 7 locations around Amsterdam red light district, for the prediction horizon of up to 30 minutes.
Civil Engineering
Advisors/Committee Members: Duives, D.C. (mentor), Krishnakumari, P.K. (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: pedestrian; forecasting; ARIMA; multiple linear regression
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APA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Wang, X. (. (2020). Forecasting tourist counts with historical counts and external features. (Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:858b0720-5ee5-49d1-bef3-c3a031717573
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Wang, Xinyi (author). “Forecasting tourist counts with historical counts and external features.” 2020. Thesis, Delft University of Technology. Accessed April 11, 2021.
http://resolver.tudelft.nl/uuid:858b0720-5ee5-49d1-bef3-c3a031717573.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Wang, Xinyi (author). “Forecasting tourist counts with historical counts and external features.” 2020. Web. 11 Apr 2021.
Vancouver:
Wang X(. Forecasting tourist counts with historical counts and external features. [Internet] [Thesis]. Delft University of Technology; 2020. [cited 2021 Apr 11].
Available from: http://resolver.tudelft.nl/uuid:858b0720-5ee5-49d1-bef3-c3a031717573.
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(. Forecasting tourist counts with historical counts and external features. [Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:858b0720-5ee5-49d1-bef3-c3a031717573
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
22.
Torquato, Roberto Matheus Nunes.
Estimação do efeito das motocicletas na capacidade de interseções semaforizadas.
Degree: 2019, Brazil
URL: http://www.repositorio.ufc.br/handle/riufc/52883
► Submitted by Zacarias Barbosa Matias Junior ([email protected]) on 2020-06-29T16:20:57Z No. of bitstreams: 1 2019_dis_rmntorquato.pdf: 2625367 bytes, checksum: 670089a84e78f928bd80d229fce9a670 (MD5)
Rejected by Marlene Sousa ([email protected]), reason:…
(more)
▼ Submitted by Zacarias Barbosa Matias Junior ([email protected]) on 2020-06-29T16:20:57Z No. of bitstreams: 1 2019_dis_rmntorquato.pdf: 2625367 bytes, checksum: 670089a84e78f928bd80d229fce9a670 (MD5)
Rejected by Marlene Sousa ([email protected]), reason: Prezado Roberto, existe a RESOLUÇÃO No 17/CEPE, 02 DE OUTUBRO DE 2017, que estabelece a normalização das dissertações e teses da UFC, em suas páginas pré-textuais e lista de referências, pelas regras da ABNT. Por esse motivo, sugerimos adequar seu trabalho ao modelo do template, disponível em: http://www.biblioteca.ufc.br/educacao-de-usuarios/templates/ Vamos agora as correções, que vc deve realizar, sempre de acordo com o template: 1. Na capa, coloque nome do PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE TRANSPORTES no local de CURSO DE ENGENHARIA CIVIL 2. Na folha de rosto, que segue a capa, e na folha de aprovação da banca, para evitar redundância em nosso idioma, coloque na folha rosto (que segue a
capa) e na folha de aprovação da banca o texto como está no template: Dissertação apresentada ao... evitando o uso da expressão: Dissertação de mestrado apresentada... 3. Na Ficha catalográfica, coloque seu nome completo. 4. Na folha de AGRADECIMENTOS, caso seja bolsista, é obrigatório inserir um agradecimento à instituição referente ao apoio recebido pela bolsa. Se a instituição for a CAPES, a Portaria nº 206, de 4 de setembro de 2018 informa que é obrigatório inserir um agradecimento à instituição referente ao apoio recebido pelo bolsista. A redação do agradecimento está expressa na portaria: O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Código de Financiamento 001. Caso não tenha bolsa favor desconsiderar essa recomendação. 5. No RESUMO e ABSTRACT os termos a serem utilizados, em negrito são: Palavras-chave e Keywords, estes devem ser alinhados à esquerda sem parágrafo. 6. Nas LISTAS DE FIGURAS,
GRÁFICOS e TABELAS observe o alinhamento da margem dos títulos das figuras, gráficos e tabelas, de modo que ao aumentar o número de dígitos das figuras elas fiquem no mesmo alinhamento de quando tinham um dígito. Ex Figura 1 e 10. Quando o título da figura ou da tabela não couber na mesma linha, sua continuação deve ficar na mesma margem da primeira letra da linha de cima do título e não voltar para a margem do F de Figura ou do T de Tabela. 7. No SUMÁRIO vc deve observar o alinhamento, para quando crescerem os dígitos das seções fique o mesmo alinhamento de quando tinha apenas um dígito. Inclusive quando o título não couber na mesma linha, sua continuação deve ficar na mesma margem da primeira letra da palavra da linha de cima do título. A palavra REFERENCIAS deve ficar na margem abaixo da letra C de Conclusões. 8. Na Lista de REFERENCIAS corrigir em toda a lista o que se pede: Todos os títulos devem ser destacados com negrito. Quando for artigo de revistas, o nome da revista é que
fica em negrito e não o título do artigo. O nome da revista não deve ser em caixa alta. Corrija em…
Advisors/Committee Members: Castro Neto, Manoel Mendonça de.
Subjects/Keywords: Transportes; Semáforo; Saturation flow; Linear regression
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APA ·
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MLA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Torquato, R. M. N. (2019). Estimação do efeito das motocicletas na capacidade de interseções semaforizadas. (Masters Thesis). Brazil. Retrieved from http://www.repositorio.ufc.br/handle/riufc/52883
Chicago Manual of Style (16th Edition):
Torquato, Roberto Matheus Nunes. “Estimação do efeito das motocicletas na capacidade de interseções semaforizadas.” 2019. Masters Thesis, Brazil. Accessed April 11, 2021.
http://www.repositorio.ufc.br/handle/riufc/52883.
MLA Handbook (7th Edition):
Torquato, Roberto Matheus Nunes. “Estimação do efeito das motocicletas na capacidade de interseções semaforizadas.” 2019. Web. 11 Apr 2021.
Vancouver:
Torquato RMN. Estimação do efeito das motocicletas na capacidade de interseções semaforizadas. [Internet] [Masters thesis]. Brazil; 2019. [cited 2021 Apr 11].
Available from: http://www.repositorio.ufc.br/handle/riufc/52883.
Council of Science Editors:
Torquato RMN. Estimação do efeito das motocicletas na capacidade de interseções semaforizadas. [Masters Thesis]. Brazil; 2019. Available from: http://www.repositorio.ufc.br/handle/riufc/52883
North-West University
23.
Van der Westhuizen, Magdelena Marianna.
Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen
.
Degree: 2011, North-West University
URL: http://hdl.handle.net/10394/6689
► Good quality management decisions often rely on the evaluation and interpretation of data. One of the most popular ways to investigate possible relationships in a…
(more)
▼ Good quality management decisions often rely on the evaluation and interpretation of data. One of the most popular ways to investigate possible relationships in a given data set is to follow a process of fitting models to the data. Regression models are often employed to assist with decision making. In addition to decision making, regression models can also be used for the optimization and prediction of data. The success of a regression model, however, relies heavily on assumptions made by the model builder. In addition, the model may also be influenced by the presence of outliers; a more robust model, which is not as easily affected by outliers, is necessary in making more accurate interpretations about the data. In this research study robust techniques for regression models with minimal assumptions are explored. Mathematical programming techniques such as linear programming, mixed integer linear programming, and piecewise linear regression are used to formulate a nonlinear regression model. Outlier detection and smoothing techniques are included to address the robustness of the model and to improve predictive accuracy. The performance of the model is tested by applying it to a variety of data sets and comparing the results to those of other models. The results of the empirical experiments are also presented in this study.
Subjects/Keywords: Robust regression;
Outlier detection;
Piecewise linear regression;
Linear programming;
Smoothing techniques;
Optimization
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APA ·
Chicago ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Van der Westhuizen, M. M. (2011). Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen
. (Thesis). North-West University. Retrieved from http://hdl.handle.net/10394/6689
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Van der Westhuizen, Magdelena Marianna. “Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen
.” 2011. Thesis, North-West University. Accessed April 11, 2021.
http://hdl.handle.net/10394/6689.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Van der Westhuizen, Magdelena Marianna. “Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen
.” 2011. Web. 11 Apr 2021.
Vancouver:
Van der Westhuizen MM. Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen
. [Internet] [Thesis]. North-West University; 2011. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10394/6689.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Van der Westhuizen MM. Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen
. [Thesis]. North-West University; 2011. Available from: http://hdl.handle.net/10394/6689
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Victoria University of Wellington
24.
Bancolita, Joel E.
Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs).
Degree: 2011, Victoria University of Wellington
URL: http://hdl.handle.net/10063/1913
► The Philippines is a country where a quarter to one-third of the population is poor. Although the nation has managed to lower poverty incidence in…
(more)
▼ The Philippines is a country where a quarter to one-third of the population
is poor. Although the nation has managed to lower poverty incidence
in some years, its booming population increases the poor population dramatically.
This is why alleviating poverty is a pinnacle program in the
country.
In aid of poverty alleviation endeavor, this study focuses on assessing
which programs had been effective in alleviating poverty given other
family characteristics. Aside from descriptive methods, employing Generalised
Linear Models (GLMs) and categorical data analysis are the focus
in analysing the effects of existing intervention programs on status of
improvement and income of families. In addition, varying effects of programs
depending on values of other covariates are also analysed.
Descriptive analysis and modeling are applied on the panel data of
families. Intervention programs namely scholarship, Comprehensive Agrarian
Reform Program (CARP) and government housing or other housing financing
program (GHFP) have been run together with other family characteristics
to describe improvement in welfare and income. Interaction
effects, between access to intervention programs and other aspects of the
family, have been derived to give a richer picture of the phenomenon. The
study has come to conclude that the programs are indeed effective in improving
lives of families, with some effects varying on some levels of other
explanatory variables.
Advisors/Committee Members: Hirose, Yuichi, Liu, I-Ming.
Subjects/Keywords: Generalized linear models; Linear regression; Logistic regression; Logit; Odds ratio; Poverty; GLM
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Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Bancolita, J. E. (2011). Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs). (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/1913
Chicago Manual of Style (16th Edition):
Bancolita, Joel E. “Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs).” 2011. Masters Thesis, Victoria University of Wellington. Accessed April 11, 2021.
http://hdl.handle.net/10063/1913.
MLA Handbook (7th Edition):
Bancolita, Joel E. “Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs).” 2011. Web. 11 Apr 2021.
Vancouver:
Bancolita JE. Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs). [Internet] [Masters thesis]. Victoria University of Wellington; 2011. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/10063/1913.
Council of Science Editors:
Bancolita JE. Poverty Diagnostics in the Philippines: Assessing Impacts of Programs through Generalised Linear Models (GLMs). [Masters Thesis]. Victoria University of Wellington; 2011. Available from: http://hdl.handle.net/10063/1913
25.
Nava, Aira [UNESP].
Variabilidade espacial de níveis freáticos do Sistema Aquífero Bauru por meio de modelo híbrido multivariado.
Degree: 2018, Universidade Estadual Paulista (UNESP)
URL: http://hdl.handle.net/11449/166386
► Submitted by Aira Nava ([email protected]) on 2018-12-05T12:23:13Z No. of bitstreams: 1 aira_final.pdf: 2893014 bytes, checksum: 5c43f8eabb6f27940c05cdeb6e2184fa (MD5)
Approved for entry into archive by Maria Lucia…
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▼ Submitted by Aira Nava ([email protected]) on 2018-12-05T12:23:13Z No. of bitstreams: 1 aira_final.pdf: 2893014 bytes, checksum: 5c43f8eabb6f27940c05cdeb6e2184fa (MD5)
Approved for entry into archive by Maria Lucia Martins Frederico null ([email protected]) on 2018-12-05T12:35:57Z (GMT) No. of bitstreams: 1 nava_a_dr_botfca.pdf: 2893014 bytes, checksum: 5c43f8eabb6f27940c05cdeb6e2184fa (MD5)
Made available in DSpace on 2018-12-05T12:35:57Z (GMT). No. of bitstreams: 1 nava_a_dr_botfca.pdf: 2893014 bytes, checksum: 5c43f8eabb6f27940c05cdeb6e2184fa (MD5) Previous issue date: 2018-09-25
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Geostatistics allows inferring unknown values with spatial structure, supporting the natural phenomena description. Geostatistical interpolators increase the understanding about the studied object, since its mathematical background ensures reliability to the method and its use associated
to the physical understanding of the problem provides significant results. Geostatistical tools have been widely used in groundwater monitoring and studies. From the hypothesis that groundwater levels can be explained by a deterministic model and spatialized with geostatistics, this work aimed to map the water table through a hybrid regression-kriging model. Soil, topographic, water and vegetation monitoring data (obtained by remote sensing) were used as predictive variables of groundwater levels. Information were collected at Guarantã, Bugre, Boi, Santana and Passarinho watersheds. The most relevant variables for the multiple regression model were chosen through principal components analysis, which determined those with greater variability. The results indicated a robust fit to the data by the model and robust predictive capacity for new observations. The adjustment of the variograms allowed the ordinary kriging of the mean water levels and the residuals of the deterministic model,
allowing a final prediction map of the groundwater.
A geoestatística permite inferir valores desconhecidos que apresentam estrutura espacial, auxiliando, assim, na descrição dos fenômenos naturais. A utilização de seus interpoladores permite um melhor entendimento do objeto de estudo, pois seu embasamento matemático garante a confiabilidade do método e sua utilização associada ao entendimento físico do problema proporciona resultados significativos. As ferramentas geoestatísticas vem sendo amplamente utilizadas no monitoramento e nos estudos dos recursos hídricos. Partindo-se da hipótese de que os níveis de água subterrânea podem ser explicados por um modelo determinístico e espacializados por ferramentas da geoestatística, o trabalho teve como objetivo o mapeamento do lençol freático através de um modelo híbrido de regressão-krigagem. Dados relacionados ao relevo, ao solo, às series de monitoramento da água e à vegetação, obtidos por sensoriamento remoto, totalizaram 21 variáveis
preditivas dos níveis do lençol freático. As informações sobre as águas subterrâneas foram coletadas por…
Advisors/Committee Members: Universidade Estadual Paulista (UNESP), Manzione, Rodrigo Lilla [UNESP].
Subjects/Keywords: Águas subterrâneas; Geoestatística; Regressão linear múltipla; Regressão-krigagem; Groundwater; Geostatistics; Multiple linear regression; Regression-kriging
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APA (6th Edition):
Nava, A. [. (2018). Variabilidade espacial de níveis freáticos do Sistema Aquífero Bauru por meio de modelo híbrido multivariado. (Doctoral Dissertation). Universidade Estadual Paulista (UNESP). Retrieved from http://hdl.handle.net/11449/166386
Chicago Manual of Style (16th Edition):
Nava, Aira [UNESP]. “Variabilidade espacial de níveis freáticos do Sistema Aquífero Bauru por meio de modelo híbrido multivariado.” 2018. Doctoral Dissertation, Universidade Estadual Paulista (UNESP). Accessed April 11, 2021.
http://hdl.handle.net/11449/166386.
MLA Handbook (7th Edition):
Nava, Aira [UNESP]. “Variabilidade espacial de níveis freáticos do Sistema Aquífero Bauru por meio de modelo híbrido multivariado.” 2018. Web. 11 Apr 2021.
Vancouver:
Nava A[. Variabilidade espacial de níveis freáticos do Sistema Aquífero Bauru por meio de modelo híbrido multivariado. [Internet] [Doctoral dissertation]. Universidade Estadual Paulista (UNESP); 2018. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/11449/166386.
Council of Science Editors:
Nava A[. Variabilidade espacial de níveis freáticos do Sistema Aquífero Bauru por meio de modelo híbrido multivariado. [Doctoral Dissertation]. Universidade Estadual Paulista (UNESP); 2018. Available from: http://hdl.handle.net/11449/166386
NSYSU
26.
Ching, Yi-Ching.
Factors Affecting the Carrying Capacity of a Rapid Transit System: The Case Study of Kaohsiung Rapid Transit System.
Degree: Master, Economics, 2014, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-143301
► This study develops a multiple regression model and then applies the method of stepwise regression to study the factors affecting the carrying capacity of Kaohsiung…
(more)
▼ This study develops a multiple
regression model and then applies the method
of stepwise
regression to study the factors affecting the carrying capacity
of Kaohsiung rapid transit system. Based on the period from April,2008 to
November,2013, the empirical results indicate that population, tourists,
hospital and business setup items of Kaohsiung city have significant
positive impacts on the carrying capacity of Kaohsiung rapid transit system.
The developed
regression model has good explanatory power.
Advisors/Committee Members: Hu,YuHau (chair), Wu, Jyh-Lin (committee member), Shu-Ling Chiang (chair).
Subjects/Keywords: stepwise regression; carrying capacity; ordinary least squares; Multiple linear regression
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APA (6th Edition):
Ching, Y. (2014). Factors Affecting the Carrying Capacity of a Rapid Transit System: The Case Study of Kaohsiung Rapid Transit System. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-143301
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Ching, Yi-Ching. “Factors Affecting the Carrying Capacity of a Rapid Transit System: The Case Study of Kaohsiung Rapid Transit System.” 2014. Thesis, NSYSU. Accessed April 11, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-143301.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Ching, Yi-Ching. “Factors Affecting the Carrying Capacity of a Rapid Transit System: The Case Study of Kaohsiung Rapid Transit System.” 2014. Web. 11 Apr 2021.
Vancouver:
Ching Y. Factors Affecting the Carrying Capacity of a Rapid Transit System: The Case Study of Kaohsiung Rapid Transit System. [Internet] [Thesis]. NSYSU; 2014. [cited 2021 Apr 11].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-143301.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Ching Y. Factors Affecting the Carrying Capacity of a Rapid Transit System: The Case Study of Kaohsiung Rapid Transit System. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0629114-143301
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Pretoria
27.
Van Zyl, W.R. (Warren Reece).
Single-Phase
convective heat transfer and pressure drop coefficients in
concentric annual.
Degree: Mechanical and Aeronautical
Engineering, 2013, University of Pretoria
URL: http://hdl.handle.net/2263/33350
► Varying diameter ratios associated with smooth concentric tube-in-tube heat exchangers are known to have an effect on its convective heat transfer capabilities. Much literature exists…
(more)
▼ Varying diameter ratios associated with smooth
concentric tube-in-tube heat exchangers
are known to have an
effect on its convective heat transfer capabilities. Much
literature
exists for predicting the inner tube’s heat transfer
coefficients, however, limited research
has been conducted for the
annulus and some of the existing correlations are known to
have
large errors.
Linear and nonlinear
regression models exist for
determining the heat transfer coefficients,
however, these are
complex and time consuming methods and require much experimental
data in order to obtain accurate solutions. A direct solution to
obtain the heat transfer
coefficients in the annulus is sought
after.
In this study a large dataset of experimental measurements
on heat exchangers with
annular diameter ratios of 0.483, 0.579,
0.593 and 0.712 was gathered. The annular
diameter ratio is
defined as the ratio of the outer diameter of the inner tube to the
inner
diameter of the outer tube. Using various methods, the data
was processed to determine
local and average Nusselt numbers in
the turbulent flow regime. These methods included
the modified
Wilson plot technique, a nonlinear
regression scheme, as well as
the log mean
temperature difference method. The inner tube
Reynolds number exponent was assumed
to be a constant 0.8 for both
the modified Wilson plot and nonlinear
regression methods.
The
logarithmic mean temperature difference method was used for both a
mean analysis on
the full length of the heat exchanger, and a
local analysis on finite control volumes. Friction
factors were
calculated directly from measured pressure drops across the
annuli.
The heat exchangers were tested for both a heated and
cooled annulus, and arranged in a
horizontal counter-flow
configuration with water as the working medium. Data was
gathered
for Reynolds numbers (based on the hydraulic diameter) varying from
10 000 to 28
000 for a heated annulus and 10 000 to 45 000 for a
cooled annulus. Local inner wall
temperatures which are generally
difficult to determine, were measured with
thermocouples embedded
within the wall. Flow obstructions within the annuli were
minimized, with only the support structures maintaining
concentricity of the inner and outer
tubes impeding
flow.
Advisors/Committee Members: Dirker, Jaco (advisor), Meyer, Josua P. (coadvisor).
Subjects/Keywords: Energy; Heat
transfer; Nonlinear
regression models; Linear
regression models;
UCTD
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APA ·
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MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Van Zyl, W. R. (. R. (2013). Single-Phase
convective heat transfer and pressure drop coefficients in
concentric annual. (Masters Thesis). University of Pretoria. Retrieved from http://hdl.handle.net/2263/33350
Chicago Manual of Style (16th Edition):
Van Zyl, W R (Warren Reece). “Single-Phase
convective heat transfer and pressure drop coefficients in
concentric annual.” 2013. Masters Thesis, University of Pretoria. Accessed April 11, 2021.
http://hdl.handle.net/2263/33350.
MLA Handbook (7th Edition):
Van Zyl, W R (Warren Reece). “Single-Phase
convective heat transfer and pressure drop coefficients in
concentric annual.” 2013. Web. 11 Apr 2021.
Vancouver:
Van Zyl WR(R. Single-Phase
convective heat transfer and pressure drop coefficients in
concentric annual. [Internet] [Masters thesis]. University of Pretoria; 2013. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/2263/33350.
Council of Science Editors:
Van Zyl WR(R. Single-Phase
convective heat transfer and pressure drop coefficients in
concentric annual. [Masters Thesis]. University of Pretoria; 2013. Available from: http://hdl.handle.net/2263/33350
University of Wollongong
28.
Riyapan, Preeya.
Model choices for complex survey analysis.
Degree: PhD, 2016, University of Wollongong
URL: ;
https://ro.uow.edu.au/theses/4670
► Survey data are an important source of information for modern society. However, the complex structures of modern populations require sampling designs for surveys that…
(more)
▼ Survey data are an important source of information for modern society. However, the complex structures of modern populations require sampling designs for surveys that are more complex than simple random sampling in order to be effective. With large national population surveys, the sample data collected via these designs typically include sample weights that allow analysis to take account of these complex population structures. As a consequence, these sample weights need to be taken into consideration when modelling the sample data, e.g. when the target of estimation is the coefficients of a regression model for the target population. In this situation, it is important to know whether these weights should be used when identifying an appropriate model specification and also whether they should be used when fitting this model to the survey data. Given the complexity of both model choice and model fitting and the limited literature on this issue, there is clearly scope for theoretical and methodological development in order to help with these decisions.
The principal aim of this thesis is to develop and evaluate strategies for population modelling using complex sample survey data. More specifically, since both linear and logistic regression analysis are very widely used statistical modelling methods, our goal is to develop procedures for analysing complex sample survey data in order to choose appropriate linear and logistic regression models based on either unweighted or weighted modelling of the survey data. In particular we develop two approaches to regression model choice and consequent regression model fit given complex survey data. These are a likelihood-based approach and a prediction-based approach. Both approaches allow us to identify a final model given two competing models suggested by model search methods based on application of different inferential paradigms. The likelihood approach is based on the non-nested test suggested by Vuong (1989), while the predictive approach uses cross-validation. The two model choice methods differ in terms of whether or not they use the sample weights. That is, we investigate four modelling strategies defined by the combination of two different approaches to model identification (likelihood-based versus cross-validation) and two paradigms for model search (unweighted versus weighted).
Subjects/Keywords: model choices; complex survey; population modelling; linear regression; logistic regression
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APA ·
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Manager
APA (6th Edition):
Riyapan, P. (2016). Model choices for complex survey analysis. (Doctoral Dissertation). University of Wollongong. Retrieved from ; https://ro.uow.edu.au/theses/4670
Chicago Manual of Style (16th Edition):
Riyapan, Preeya. “Model choices for complex survey analysis.” 2016. Doctoral Dissertation, University of Wollongong. Accessed April 11, 2021.
; https://ro.uow.edu.au/theses/4670.
MLA Handbook (7th Edition):
Riyapan, Preeya. “Model choices for complex survey analysis.” 2016. Web. 11 Apr 2021.
Vancouver:
Riyapan P. Model choices for complex survey analysis. [Internet] [Doctoral dissertation]. University of Wollongong; 2016. [cited 2021 Apr 11].
Available from: ; https://ro.uow.edu.au/theses/4670.
Council of Science Editors:
Riyapan P. Model choices for complex survey analysis. [Doctoral Dissertation]. University of Wollongong; 2016. Available from: ; https://ro.uow.edu.au/theses/4670
Rice University
29.
Joshi, Babhru.
A Convex Algorithm for Mixed Linear Regression.
Degree: MA, Engineering, 2017, Rice University
URL: http://hdl.handle.net/1911/95962
► Mixed linear regression is a high dimensional affine space clustering problem where the goal is to find the parameters of multiple affine spaces that best…
(more)
▼ Mixed
linear regression is a high dimensional affine space clustering problem where the goal is to find the parameters of multiple affine spaces that best fit a collection of points. We introduce a convex 2nd order cone program (based on l1/fused lasso) which allows us to reformulate the mixed
linear regression as an Rd clustering problem. The convex program is parameter free and does not require prior knowledge of the number of clusters, which is more tractable while clustering in Rd. In the noiseless case, we prove that the convex program recovers the
regression coefficients exactly under narrow technical conditions of well-separation and balance. We demonstrate numerical performance on BikeShare data and music tone perception data.
Advisors/Committee Members: Hand, Paul E (advisor).
Subjects/Keywords: mixed linear regression; mixed regression; mixture model; fused lasso
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APA ·
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APA (6th Edition):
Joshi, B. (2017). A Convex Algorithm for Mixed Linear Regression. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/95962
Chicago Manual of Style (16th Edition):
Joshi, Babhru. “A Convex Algorithm for Mixed Linear Regression.” 2017. Masters Thesis, Rice University. Accessed April 11, 2021.
http://hdl.handle.net/1911/95962.
MLA Handbook (7th Edition):
Joshi, Babhru. “A Convex Algorithm for Mixed Linear Regression.” 2017. Web. 11 Apr 2021.
Vancouver:
Joshi B. A Convex Algorithm for Mixed Linear Regression. [Internet] [Masters thesis]. Rice University; 2017. [cited 2021 Apr 11].
Available from: http://hdl.handle.net/1911/95962.
Council of Science Editors:
Joshi B. A Convex Algorithm for Mixed Linear Regression. [Masters Thesis]. Rice University; 2017. Available from: http://hdl.handle.net/1911/95962
University of Alberta
30.
Ávila Pires, Bernardo.
Statistical analysis of L1-penalized linear estimation with
applications.
Degree: MS, Department of Computing Science, 2011, University of Alberta
URL: https://era.library.ualberta.ca/files/dr26xz283
► We study linear estimation based on perturbed data when performance is measured by a matrix norm of the expected residual error, in particular, the case…
(more)
▼ We study linear estimation based on perturbed data
when performance is measured by a matrix norm of the expected
residual error, in particular, the case in which there are many
unknowns, but the “best” estimator is sparse, or has small L1-norm.
We propose a Lasso-like procedure that finds the minimizer of an
L1-penalized squared norm of the residual. For linear regression we
show O(sqrt(1/n)) uniform bounds for the difference between the
residual error norm of our estimator and that of the “best”
estimator. These also hold for on-policy value function
approximation in reinforcement learning. In the off-policy case, we
show O(sqrt((ln n)/n)) bounds for the expected difference. Our
analysis has a unique feature: it is the same for both regression
and reinforcement learning. We took care to separate the
deterministic and probabilistic arguments, so as to analyze a range
of seemingly different linear estimation problems in a unified
way.
Subjects/Keywords: linear estimation; linear regression; machine learning; Lasso; excess risk; reinforcement learning
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APA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Ávila Pires, B. (2011). Statistical analysis of L1-penalized linear estimation with
applications. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/dr26xz283
Chicago Manual of Style (16th Edition):
Ávila Pires, Bernardo. “Statistical analysis of L1-penalized linear estimation with
applications.” 2011. Masters Thesis, University of Alberta. Accessed April 11, 2021.
https://era.library.ualberta.ca/files/dr26xz283.
MLA Handbook (7th Edition):
Ávila Pires, Bernardo. “Statistical analysis of L1-penalized linear estimation with
applications.” 2011. Web. 11 Apr 2021.
Vancouver:
Ávila Pires B. Statistical analysis of L1-penalized linear estimation with
applications. [Internet] [Masters thesis]. University of Alberta; 2011. [cited 2021 Apr 11].
Available from: https://era.library.ualberta.ca/files/dr26xz283.
Council of Science Editors:
Ávila Pires B. Statistical analysis of L1-penalized linear estimation with
applications. [Masters Thesis]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/dr26xz283
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Open Access Theses and Dissertations