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Rutgers University
1.
Yan, Xi, 1985-.
Statistical analysis of dynamic risk neutral density, dynamic cross-sectional distribution and portfolio optimization.
Degree: PhD, Statistics and Biostatistics, 2019, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/62066/ 
► This dissertation focuses on developing new statistical methods for analyzing and modeling financial time series. The first part of this dissertation discusses modeling of functional…
(more)
▼ This dissertation focuses on developing new statistical methods for analyzing and modeling financial time series. The first part of this dissertation discusses modeling of functional and distributional time series, assuming the series are driven by a finite dimensional underlying feature process. Functional time series are commonly observed in finance and difficult to model mainly due to high dimensionality. We instead focus on a low-dimensional latent feature process and connect it with the original functional time series through generalized state-space models. A state-space model assumes that observations are driven by an underlying dynamic state process and is widely used in many fields. We propose a generalized two-stage Sequential Monte Carlo (SMC) joint estimation framework to model functional time series driven by its feature process through state-space models and perform on-line estimations and predictions. In order to improve computation efficiency, we also implement parallel computing and re-design computation algorithms to integrate with non-linear optimization and SMC calculations.
Two financial applications are presented to demonstrate the robustness and efficiency of our proposed framework. The first application aims to extract and model the daily implied risk neutral densities from observed call option prices. We view the underlying risk neutral density as a functional time series driven by its feature process and model it with a parametric mixed log-normal distribution through a state-space model. We conduct both simulation and empirical studies and compare prediction performance of our models with that of random walk models. Empirically, the proposed models improves prediction performance significantly. The second financial application studies daily cross-sectional distribution of 1000 largest market capitalization stock returns from year 1991 to year 2002. Similarly we view cross-sectional distribution as a functional time series driven by its feature process and model it with a four-parameter generalized skewed t-distribution. Using proposed two-stage SMC joint estimation framework, we build models separately for different market conditions, including the dot-com crisis. In both bearish and bullish markets, prediction performances of our models gain substantial improvement comparing with random walk models.
The second part of dissertation presents a new portfolio optimization strategy for minimum variance portfolios with constraints on short-sale and transaction costs. Unlike traditional mean-variance theory, our method minimizes only the portfolio risk and uses analysts' consensus ratings to pre-screen stocks. An empirical study of S&P 500 stocks from year 1990 to year 2009 is conducted to demonstrate effectiveness. We show that portfolios constructed and optimized using our strategy deliver considerable improvement of performance in terms of Sharpe ratio comparing with benchmark portfolios and portfolios in past literatures.
Advisors/Committee Members: Chen, Rong (chair), Xiao, Han (internal member), Tan, Zhiqiang (internal member), Lin, Ming (outside member), School of Graduate Studies.
Subjects/Keywords: Functional time series; Time-series analysis
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APA (6th Edition):
Yan, Xi, 1. (2019). Statistical analysis of dynamic risk neutral density, dynamic cross-sectional distribution and portfolio optimization. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/62066/
Chicago Manual of Style (16th Edition):
Yan, Xi, 1985-. “Statistical analysis of dynamic risk neutral density, dynamic cross-sectional distribution and portfolio optimization.” 2019. Doctoral Dissertation, Rutgers University. Accessed February 27, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/62066/.
MLA Handbook (7th Edition):
Yan, Xi, 1985-. “Statistical analysis of dynamic risk neutral density, dynamic cross-sectional distribution and portfolio optimization.” 2019. Web. 27 Feb 2021.
Vancouver:
Yan, Xi 1. Statistical analysis of dynamic risk neutral density, dynamic cross-sectional distribution and portfolio optimization. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2021 Feb 27].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/62066/.
Council of Science Editors:
Yan, Xi 1. Statistical analysis of dynamic risk neutral density, dynamic cross-sectional distribution and portfolio optimization. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/62066/
2.
Gorrostieta, Cristina.
Dependence in Complex Multivariate Time Series.
Degree: PhD, Biostatistics, 2012, Brown University
URL: https://repository.library.brown.edu/studio/item/bdr:297536/
► In this dissertation work, I develop novel extensions of two classical techniques for the statistical analysis of dependencies in multivariate time series, namely vector autoregressive…
(more)
▼ In this dissertation work, I develop novel extensions
of two classical techniques for the statistical analysis of
dependencies in multivariate
time series, namely vector
autoregressive model (VAR) and coherence analysis. I demonstrate
the utility of these methods to brain signals.
I generalize the vector autoregressive model by embedding it
in a mixed-effects framework to account for variability between
subjects. The traditional VAR approach for exploring brain
connectivity assumes that brain signals dependencies are identical
across all subjects. Thus, it does not provide a proper framework
to identify connectivity structures common across a group nor
connectivity structures with high variability between subjects. My
proposed mixed-effects VAR model overcomes these limitations.
To generalize the coherence analysis, I developed the lagged
coherence measure. In the signal processing literature, the notion
of dual frequency coherence has been developed to explore
oscillatory relationships between different frequencies across
signals. I extended this concept of dual frequency coherence to
lagged coherence. Using lagged coherence, I explored oscillatory
relationships between different frequencies, at lagged
time
intervals between the components of
time series. My proposed method
can be utilized to investigate how brain oscillatory activity, at
certain frequency in the current period of
time, may predict brain
oscillatory activity at another frequency, in the future period of
time.
Advisors/Committee Members: Gatsonis, Constantine (Director), Kim, Eunhee (Reader), Dickstein, Daniel (Reader), Ombao, Hernando (Reader).
Subjects/Keywords: Multivariate Time Series
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APA (6th Edition):
Gorrostieta, C. (2012). Dependence in Complex Multivariate Time Series. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:297536/
Chicago Manual of Style (16th Edition):
Gorrostieta, Cristina. “Dependence in Complex Multivariate Time Series.” 2012. Doctoral Dissertation, Brown University. Accessed February 27, 2021.
https://repository.library.brown.edu/studio/item/bdr:297536/.
MLA Handbook (7th Edition):
Gorrostieta, Cristina. “Dependence in Complex Multivariate Time Series.” 2012. Web. 27 Feb 2021.
Vancouver:
Gorrostieta C. Dependence in Complex Multivariate Time Series. [Internet] [Doctoral dissertation]. Brown University; 2012. [cited 2021 Feb 27].
Available from: https://repository.library.brown.edu/studio/item/bdr:297536/.
Council of Science Editors:
Gorrostieta C. Dependence in Complex Multivariate Time Series. [Doctoral Dissertation]. Brown University; 2012. Available from: https://repository.library.brown.edu/studio/item/bdr:297536/
Addis Ababa University
3.
Tesfaye, Alemayehu.
Determinant of tax revenue in Ethiopia
.
Degree: 2015, Addis Ababa University
URL: http://etd.aau.edu.et/dspace/handle/123456789/6819
► The focus of paper is to identify determinants of tax revenue in Ethiopia by using a secondary data and multiple variables regression model. The objective…
(more)
▼ The focus of paper is to identify determinants of tax revenue in Ethiopia by using a secondary
data and multiple variables regression model. The objective of the study was to identify
determinants of tax revenue such sectors of economy like agriculture, industry and service, FDI,
inflation rate, interest rate, per capita income and trade openness. A study is important to
identify significant variables affecting tax revenue. The research approach adopted in this thesis
includes
series data set that consists of fifteen years. The
time period covered was 1999/00 to
2013/14; this is primarily due to unavailability of organized data before the indicated period.
Both descriptive statistics and econometric tools were employed to analyze and present
the obtained data. The findings from this research provide evidence that, foreign direct
investment to GDP percentage regression result shows negative significant, Industry sector in
percentage of GDP positive and significant, Inflation negative but not significant, Per capita
income has the positive sign which is significant, and saving interest rate have positive
insignificant impact on tax revenue. The main conclusions drawn from this study are, foreign
direct investment to GDP, Industry sector in percentage of GDP and Per capita income have
significant impact on tax revenue. This paper recommends that inflation rate and saving interest
rate are in significant variables affecting tax revenue.
Advisors/Committee Members: Laxmikantham.p (PhD.) (advisor).
Subjects/Keywords: Tax;
Time series
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APA (6th Edition):
Tesfaye, A. (2015). Determinant of tax revenue in Ethiopia
. (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/6819
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):
Tesfaye, Alemayehu. “Determinant of tax revenue in Ethiopia
.” 2015. Thesis, Addis Ababa University. Accessed February 27, 2021.
http://etd.aau.edu.et/dspace/handle/123456789/6819.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Tesfaye, Alemayehu. “Determinant of tax revenue in Ethiopia
.” 2015. Web. 27 Feb 2021.
Vancouver:
Tesfaye A. Determinant of tax revenue in Ethiopia
. [Internet] [Thesis]. Addis Ababa University; 2015. [cited 2021 Feb 27].
Available from: http://etd.aau.edu.et/dspace/handle/123456789/6819.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Tesfaye A. Determinant of tax revenue in Ethiopia
. [Thesis]. Addis Ababa University; 2015. Available from: http://etd.aau.edu.et/dspace/handle/123456789/6819
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
The Ohio State University
4.
Michel, Jonathan R.
Essays in Nonlinear Time Series Analysis.
Degree: PhD, Economics, 2019, The Ohio State University
URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555001297904158
► This dissertation consists of six papers. Each of these papers are on a different aspect of statistical analysis of nonlinear time series. In the first…
(more)
▼ This dissertation consists of six papers. Each of
these papers are on a different aspect of statistical analysis of
nonlinear
time series. In the first paper, we study the behavior of
a nonstationary
time series which has different behavior for
``high" and ``low" levels. This consists of the introduction of a
new nonlinear
time series model, a mathematical analysis of the
functional limit theorem for this model, a statistical test for
behavior similar to this new model, and a proposed technique for
robust cointegration in the presence of this new model. The second
paper consists of an extension of this idea into volatility
modeling.The third paper considers experimental design and sampling
of Markov chains. In particular, it focuses on how to feasibly
optimally sample a continuous two-state Markov chain.The fourth
paper is on integer valued
time series. The focus here is on
studying the properties of the INGARCH(1,1) model in the
nonstationary case. This consists of applying mathematical
machinery rarely used in econometrics. Additionally, in this paper
extensions towards stationarity tests are considered.The fifth
paper studies the dynamic Tobit, a
time series model often used
when data is censored below. In this paper, weak dependence and
mixing properties are shown to hold, which is relevant for studying
the statistical properties of estimation for this model.The sixth
paper studies the reciprocal of the random walk. This is relevant
in
time series econometrics as such a process is a possible model
for
time series with a stochastic diminishing trend.
Advisors/Committee Members: de Jong, Robert (Advisor).
Subjects/Keywords: Economics; Time Series Analysis, Nonstationary time series, Mixing,
Nonlinear Time Series
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Michel, J. R. (2019). Essays in Nonlinear Time Series Analysis. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1555001297904158
Chicago Manual of Style (16th Edition):
Michel, Jonathan R. “Essays in Nonlinear Time Series Analysis.” 2019. Doctoral Dissertation, The Ohio State University. Accessed February 27, 2021.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1555001297904158.
MLA Handbook (7th Edition):
Michel, Jonathan R. “Essays in Nonlinear Time Series Analysis.” 2019. Web. 27 Feb 2021.
Vancouver:
Michel JR. Essays in Nonlinear Time Series Analysis. [Internet] [Doctoral dissertation]. The Ohio State University; 2019. [cited 2021 Feb 27].
Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555001297904158.
Council of Science Editors:
Michel JR. Essays in Nonlinear Time Series Analysis. [Doctoral Dissertation]. The Ohio State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555001297904158
Euskal Herriko Unibertsitatea / Universidad del País Vasco
5.
Mora Valencia, Andrés.
Four essays on financial risk quantification
.
Degree: 2020, Euskal Herriko Unibertsitatea / Universidad del País Vasco
URL: http://hdl.handle.net/10810/49774
► Esta tesis tiene como objetivo analizar el desempeño de medidas de riesgo como el Value-at-Risk (VaR) y (recientemente propuesta por el Comité de Basilea) de…
(more)
▼ Esta tesis tiene como objetivo analizar el desempeño de medidas de riesgo como el Value-at-Risk (VaR) y (recientemente propuesta por el Comité de Basilea) de Expected Shortfall (ES), principalmente para cuantificar riesgo de mercado, con diferentes modelos distribucionales, como por ejemplo la distribución Gaussiana (como modelo base), y varias distribuciones que presentan colas pesadas como la distribución t de Student, distribución de Pareto generalizada (GPD, por sus siglas inglés), la distribución ¿-estable, distribución g-h, y la distribución Gram-Charlier. Para tal fin se emplean diferentes activos como índices bursátiles de energía tradicional y de activos financieros sostenibles. Dada la preocupación en los mercados financieros por el (ab)uso de activos como Exchange-traded funds (ETFs), en especial los ETFs apalancados (LETFs, por sus siglas en inglés), estos activos también son analizados en la presente tesis. Aunque Expected Shortfall es una medida coherente al riesgo, es conocido que esta medida no cumple con la propiedad de elicitabilidad, una propiedad deseable en pronósticos con fines de validación de modelos (backtesting). Esta tesis implementa dos recientes técnicas de validación de ES con buenos resultados e implicaciones en cuanto a estabilidad financiera. Finalmente se realiza una revisión de la reciente propuesta del Comité de Basilea para cuantificar riesgo operacional.
Advisors/Committee Members: Díaz Pérez, Antonio (advisor), Orbe Mandaluniz, Susan (advisor), Garcia-Donato Layron, Gonzalo (advisor).
Subjects/Keywords: time series;
econometric models;
economic time-series;
series temporales;
modelos econométricos;
series temporales económicas
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APA ·
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MLA ·
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Manager
APA (6th Edition):
Mora Valencia, A. (2020). Four essays on financial risk quantification
. (Doctoral Dissertation). Euskal Herriko Unibertsitatea / Universidad del País Vasco. Retrieved from http://hdl.handle.net/10810/49774
Chicago Manual of Style (16th Edition):
Mora Valencia, Andrés. “Four essays on financial risk quantification
.” 2020. Doctoral Dissertation, Euskal Herriko Unibertsitatea / Universidad del País Vasco. Accessed February 27, 2021.
http://hdl.handle.net/10810/49774.
MLA Handbook (7th Edition):
Mora Valencia, Andrés. “Four essays on financial risk quantification
.” 2020. Web. 27 Feb 2021.
Vancouver:
Mora Valencia A. Four essays on financial risk quantification
. [Internet] [Doctoral dissertation]. Euskal Herriko Unibertsitatea / Universidad del País Vasco; 2020. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/10810/49774.
Council of Science Editors:
Mora Valencia A. Four essays on financial risk quantification
. [Doctoral Dissertation]. Euskal Herriko Unibertsitatea / Universidad del País Vasco; 2020. Available from: http://hdl.handle.net/10810/49774
Nelson Mandela Metropolitan University
6.
Mlambo, Farai Fredric.
Good's casualty for time series: a regime-switching framework.
Degree: Faculty of Science, 2014, Nelson Mandela Metropolitan University
URL: http://hdl.handle.net/10948/6018
► Causal analysis is a significant role-playing field in the applied sciences such as statistics, econometrics, and technometrics. Particularly, probability-raising models have warranted significant research interest.…
(more)
▼ Causal analysis is a significant role-playing field in the applied sciences such as statistics, econometrics, and technometrics. Particularly, probability-raising models have warranted significant research interest. Most of the discussions in this area are philosophical in nature. Contemporarily, the econometric causality theory, developed by C.J.W. Granger, is popular in practical, time series causal applications. While this type of causality technique has many strong features, it has serious limitations. The processes studied, in particular, should be stationary and causal relationships are restricted to be linear. However, we cannot classify regime-switching processes as linear and stationary. I.J. Good proposed a probabilistic, event-type explication of causality that circumvents some of the limitations of Granger’s methodology. This work uses the probability raising causality ideology, as postulated by Good, to propose some causal analysis methodology applicable in a stochastic, non-stationary domain. There is a proposal made for a Good’s causality test, by transforming the originally specified probabilistic causality theory from random events to a stochastic, regime-switching framework. The researcher performed methodological validation via causality simulations for a Markov, regime-switching model. The proposed test can be used to detect whether none stochastic process is causal to the observed behaviour of another, probabilistically. In particular, the regime-switch causality explication proposed herein is pivotal to the results articulated. This research also examines the power of the proposed test by using simulations, and outlines some steps that one may take in using the test in a practical setting.
Subjects/Keywords: Time-series analysis; Econometrics
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APA ·
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Manager
APA (6th Edition):
Mlambo, F. F. (2014). Good's casualty for time series: a regime-switching framework. (Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/6018
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):
Mlambo, Farai Fredric. “Good's casualty for time series: a regime-switching framework.” 2014. Thesis, Nelson Mandela Metropolitan University. Accessed February 27, 2021.
http://hdl.handle.net/10948/6018.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Mlambo, Farai Fredric. “Good's casualty for time series: a regime-switching framework.” 2014. Web. 27 Feb 2021.
Vancouver:
Mlambo FF. Good's casualty for time series: a regime-switching framework. [Internet] [Thesis]. Nelson Mandela Metropolitan University; 2014. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/10948/6018.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Mlambo FF. Good's casualty for time series: a regime-switching framework. [Thesis]. Nelson Mandela Metropolitan University; 2014. Available from: http://hdl.handle.net/10948/6018
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Mississippi State University
7.
Wang, Jingjing.
Different steimations of time series models and application for foreign exchange in emerging markets.
Degree: MS, Mathematics and Statistics, 2016, Mississippi State University
URL: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06292016-121204/
;
► Time series models have been widely used in simulating financial data sets. Finding a nice way to estimate the parameters is really important. One…
(more)
▼ Time series models have been widely used in simulating financial data sets. Finding a nice way to estimate the parameters is really important. One of the traditional ways is to use maximum likelihood estimation to make an approach. However, when the error terms dont have normality, MLE would be less efficient. Quasi maximum likelihood estimation, also regarded as Gaussian MLE, would be more efficient. Considering the heavy-tailed financial data sets, we can use non-Gaussian quasi maximum likelihood, which needs less assumptions and conditions. We use real financial data sets to compare these estimators.
Advisors/Committee Members: Tung-Lung Wu (committee member).
Subjects/Keywords: emerging markets; time series
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APA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Wang, J. (2016). Different steimations of time series models and application for foreign exchange in emerging markets. (Masters Thesis). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-06292016-121204/ ;
Chicago Manual of Style (16th Edition):
Wang, Jingjing. “Different steimations of time series models and application for foreign exchange in emerging markets.” 2016. Masters Thesis, Mississippi State University. Accessed February 27, 2021.
http://sun.library.msstate.edu/ETD-db/theses/available/etd-06292016-121204/ ;.
MLA Handbook (7th Edition):
Wang, Jingjing. “Different steimations of time series models and application for foreign exchange in emerging markets.” 2016. Web. 27 Feb 2021.
Vancouver:
Wang J. Different steimations of time series models and application for foreign exchange in emerging markets. [Internet] [Masters thesis]. Mississippi State University; 2016. [cited 2021 Feb 27].
Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06292016-121204/ ;.
Council of Science Editors:
Wang J. Different steimations of time series models and application for foreign exchange in emerging markets. [Masters Thesis]. Mississippi State University; 2016. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06292016-121204/ ;
University of Alberta
8.
Mueller, David A.
Time Series Discords.
Degree: MS, Department of Computing Science, 2013, University of Alberta
URL: https://era.library.ualberta.ca/files/g445cd805
► Time series discords, as introduced in by Keogh et al. [5] is described as the subsequence in the time series which is maximally different from…
(more)
▼ Time series discords, as introduced in by Keogh et al.
[5] is described as the subsequence in the time series which is
maximally different from the rest of the subsequences. Discovery of
time series discords has been applied to several diverse domains
including space shuttle telemetry, industry, and medicine [5] to
detect anomalies in the data which can identify equipment failure,
unusual patterns of activity and health problems. In this thesis we
will examine the problem of finding time series discords, with
detailed analysis of the problem and analysis of the effectiveness
of prior work. Three different areas of discord discovery will be
examined: Top Discord, Variable Length Discords, and Top-K
Discords. In each of these areas, we strive to reduce the number or
ease the selection of input parameters required by the end user.
Emphasis is also placed on improved runtime and scalability of
discord discovery methods.
Subjects/Keywords: Anomaly Detection; Discord; Time Series
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Manager
APA (6th Edition):
Mueller, D. A. (2013). Time Series Discords. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/g445cd805
Chicago Manual of Style (16th Edition):
Mueller, David A. “Time Series Discords.” 2013. Masters Thesis, University of Alberta. Accessed February 27, 2021.
https://era.library.ualberta.ca/files/g445cd805.
MLA Handbook (7th Edition):
Mueller, David A. “Time Series Discords.” 2013. Web. 27 Feb 2021.
Vancouver:
Mueller DA. Time Series Discords. [Internet] [Masters thesis]. University of Alberta; 2013. [cited 2021 Feb 27].
Available from: https://era.library.ualberta.ca/files/g445cd805.
Council of Science Editors:
Mueller DA. Time Series Discords. [Masters Thesis]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/g445cd805
University of Georgia
9.
Slaughter, Justin Michael.
Small-sample prediction of estimated loss potentials.
Degree: 2014, University of Georgia
URL: http://hdl.handle.net/10724/24496
► This thesis constructs predictions for the 2003 General Liability premises and operations estimated loss potentials (ELPs) for Manufacturers and Contractors (MC) and Owners, Landlords, and…
(more)
▼ This thesis constructs predictions for the 2003 General Liability premises and operations estimated loss potentials (ELPs) for Manufacturers and Contractors (MC) and Owners, Landlords, and Tenants (OLT). The dataset contains yearly ELPs from
1990-2002 for 23 MC class codes and 57 OLT class codes, which came from three Insurance Services O ce (ISO) circulars. Bootstrapping was performed on the MC and OLT 2003 predicted ELPs to be able to construct 95% con dence intervals. In spite of the
small series, the results appear to be good.
Subjects/Keywords: Actuarial; Bootstrapping; Time-Series Analysis
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APA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Slaughter, J. M. (2014). Small-sample prediction of estimated loss potentials. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/24496
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):
Slaughter, Justin Michael. “Small-sample prediction of estimated loss potentials.” 2014. Thesis, University of Georgia. Accessed February 27, 2021.
http://hdl.handle.net/10724/24496.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Slaughter, Justin Michael. “Small-sample prediction of estimated loss potentials.” 2014. Web. 27 Feb 2021.
Vancouver:
Slaughter JM. Small-sample prediction of estimated loss potentials. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/10724/24496.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Slaughter JM. Small-sample prediction of estimated loss potentials. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/24496
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas A&M University
10.
Fang, Lu.
Three Essays on Time Series Analysis of Chinese Financial Markets.
Degree: PhD, Agricultural Economics, 2017, Texas A&M University
URL: http://hdl.handle.net/1969.1/161318
► This dissertation studies three important issues in Chinese financial markets. The interdependence structure and information transmission among Chinese cross-listed stocks in Shanghai, Hong Kong and…
(more)
▼ This dissertation studies three important issues in Chinese financial markets. The interdependence structure and information transmission among Chinese cross-listed stocks in Shanghai, Hong Kong and New York is examined. Results indicate that the home bias hypothesis, which suggests the dominant role of home market in pricing information transmission, is strongly supported in contemporaneous
time, modestly supported at the short horizon and not supported at the long horizon. The Shanghai market as the home market is highly exogenous at all horizons. Moreover, the Hong Kong market leads the New York market in contemporaneous
time.
Whether interest rates help to forecast stock returns in China is studied using the prequential approach. With respect to calibration (reliability), it is found that including interest rates in the model improves the model’s ability to issue realistic probability forecasts of stock returns – a model of stock returns that does not include interest rates as an explanatory variable is not as well calibrated as a model that does include interest rates in the stock returns equation. With regard to sorting (resolution), results suggest that the model that includes interest rates performs better in distinguishing stock returns that actually occur and stock returns that do not occur when compared to a model that does not include interest rates in the stock returns equation. Overall, the interest rates help in forecasting stock returns in China in terms of both calibration and sorting.
Two factor analysis methods are investigated through forecasting Chinese interest rate based on a factor-augmented vector autoregression (FAVAR). Factors are estimated from 288 Chinese security
series to reflect the common forces that drive the movements and dynamics in the Chinese equity market. As a result, the factor estimation method by Lam and Yao outperforms the traditional principal components analysis (PCA) in terms of forecasting accuracy, especially at the short horizons.
Advisors/Committee Members: Bessler, David (advisor), Wu, Ximing (committee member), Bryant, Henry (committee member), Leatham, David (committee member).
Subjects/Keywords: Time series; Chinese financial markets
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APA (6th Edition):
Fang, L. (2017). Three Essays on Time Series Analysis of Chinese Financial Markets. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161318
Chicago Manual of Style (16th Edition):
Fang, Lu. “Three Essays on Time Series Analysis of Chinese Financial Markets.” 2017. Doctoral Dissertation, Texas A&M University. Accessed February 27, 2021.
http://hdl.handle.net/1969.1/161318.
MLA Handbook (7th Edition):
Fang, Lu. “Three Essays on Time Series Analysis of Chinese Financial Markets.” 2017. Web. 27 Feb 2021.
Vancouver:
Fang L. Three Essays on Time Series Analysis of Chinese Financial Markets. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1969.1/161318.
Council of Science Editors:
Fang L. Three Essays on Time Series Analysis of Chinese Financial Markets. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161318
McMaster University
11.
Barrows, Dexter.
A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series.
Degree: MSc, 2016, McMaster University
URL: http://hdl.handle.net/11375/19103
► Forecasting tools play an important role in public response to epidemics. Despite this, limited work has been done in comparing best-in-class techniques across the broad…
(more)
▼ Forecasting tools play an important role in public response to epidemics. Despite this, limited work has been done in comparing best-in-class techniques across the broad spectrum of time series forecasting methodologies. Forecasting frameworks were developed that utilised three methods designed to work with nonlinear dynamics: Iterated Filtering (IF) 2, Hamiltonian MCMC (HMC), and S-mapping. These were compared in several forecasting scenarios including a seasonal epidemic and a spatiotemporal epidemic. IF2 combined with parametric bootstrapping produced superior predictions in all scenarios. S-mapping combined with Dewdrop Regression produced forecasts slightly less-accurate than IF2 and HMC, but demonstrated vastly reduced running times. Hence, S-mapping with or without Dewdrop Regression should be used to glean initial insight into future epidemic behaviour, while IF2 and parametric bootstrapping should be used to refine forecast estimates in time.
Thesis
Master of Science (MSc)
Advisors/Committee Members: Bolker, Benjamin, Mathematics and Statistics.
Subjects/Keywords: Forecasting; Time series; Estimation; Fitting
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APA (6th Edition):
Barrows, D. (2016). A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/19103
Chicago Manual of Style (16th Edition):
Barrows, Dexter. “A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series.” 2016. Masters Thesis, McMaster University. Accessed February 27, 2021.
http://hdl.handle.net/11375/19103.
MLA Handbook (7th Edition):
Barrows, Dexter. “A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series.” 2016. Web. 27 Feb 2021.
Vancouver:
Barrows D. A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series. [Internet] [Masters thesis]. McMaster University; 2016. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/11375/19103.
Council of Science Editors:
Barrows D. A Comparative Study of Techniques for Estimation and Inference of Nonlinear Stochastic Time Series. [Masters Thesis]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/19103
Queens University
12.
Pohlkamp-Hartt, Joshua.
Computationally Intensive Methods for Spectrum Estimation
.
Degree: Mathematics and Statistics, 2016, Queens University
URL: http://hdl.handle.net/1974/14291
► Spectrum estimation is an essential technique for analyzing time series data. A leading method in the field of spectrum estimation is the multitaper method. The…
(more)
▼ Spectrum estimation is an essential technique for analyzing time series data. A leading method in the field of spectrum estimation is the multitaper method. The multitaper method has been applied to many scientific fields and has led to the development of new methods for detection signals and modeling periodic data. Within these methods there are open problems concerning parameter selection, signal detection rates, and signal estimation. The focus of this thesis is to address these problems by using techniques from statistical learning theory. This thesis presents three theoretical contributions for improving methods related to the multitaper spectrum estimation method: (1) two hypothesis testing procedures for evaluating the choice of time-bandwidth, NW, and number of tapers, K, parameters for the multitaper method, (2) a bootstrapping procedure for improving the signal detection rates for the F-test for line components, and (3) cross-validation, boosting, and bootstrapping methods for improving the performance of the inverse Fourier transform periodic data estimation method resulting from the F-test. We additionally present two applied contributions: (1) a new atrial signal extraction method for electrocardiogram data, and (2) four new methods for analyzing, modeling, and reporting on hockey game play at the Major Junior level.
Subjects/Keywords: Time Series
;
Spectrum Estimation
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Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Pohlkamp-Hartt, J. (2016). Computationally Intensive Methods for Spectrum Estimation
. (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/14291
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):
Pohlkamp-Hartt, Joshua. “Computationally Intensive Methods for Spectrum Estimation
.” 2016. Thesis, Queens University. Accessed February 27, 2021.
http://hdl.handle.net/1974/14291.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Pohlkamp-Hartt, Joshua. “Computationally Intensive Methods for Spectrum Estimation
.” 2016. Web. 27 Feb 2021.
Vancouver:
Pohlkamp-Hartt J. Computationally Intensive Methods for Spectrum Estimation
. [Internet] [Thesis]. Queens University; 2016. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1974/14291.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Pohlkamp-Hartt J. Computationally Intensive Methods for Spectrum Estimation
. [Thesis]. Queens University; 2016. Available from: http://hdl.handle.net/1974/14291
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Queens University
13.
Rahim, Karim.
Applications of Multitaper Spectral Analysis to Nonstationary Data
.
Degree: Mathematics and Statistics, 2014, Queens University
URL: http://hdl.handle.net/1974/12584
► This thesis is concerned with changes in the spectrum over time observed in Holocene climate data as recorded in the Burgundy grape harvest date series.…
(more)
▼ This thesis is concerned with changes in the spectrum over time observed in Holocene climate data as recorded in the Burgundy grape harvest date series. These changes represent nonstationarities, and while spectral estimation techniques are relatively robust in the presence of nonstationarity – that is, they are able to detect significant contributions to power at a given frequency in cases where the contribution to power at that given frequency is not constant over time – estimation and prediction can be improved by considering nonstationarity. We propose improving spectral estimation by considering such changes. Specifically, we propose estimating the level of change in frequency over time, detecting change-point(s) and sectioning the time series into stationary segments. We focus on locating a change in frequency domain in time, and propose a graphical technique to detect spectral changes over time. We test the estimation technique in simulation, and then apply it to the Burgundy grape harvest date series. The Burgundy grape harvest date series was selected to demonstrate the introduced estimator and methodology because the time series is equally spaced, has few missing values, and a multitaper spectral analysis, which the methodology proposed in this thesis is based on, of the grape harvest date series was recently published. In addition, we propose a method using a test for goodness-of-fit of autoregressive estimators to aid in assessment of change in spectral properties over time.
This thesis has four components: (1) introduction and study of a level-of-change estimator for use in the frequency domain change-point detection, (2) spectral analysis of the Burgundy grape harvest date series, (3) goodness-of-fit estimates for autoregressive processes, and (4) introduction of a statistical software package for multitaper spectral analysis. We present four results. (1) We introduce and demonstrate the feasibility of a level-of-change estimator. (2) We present a spectral analysis and coherence study of the Burgundy grape harvest date series that includes locating a change-point. (3) We present a study showing an advantage using multitaper spectral estimates when calculating autocorrelation coefficients. And (4) we introduce an R software package, available on the CRAN, to perform multitaper spectral estimation.
Subjects/Keywords: Spectral Analysis
;
Time Series
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APA (6th Edition):
Rahim, K. (2014). Applications of Multitaper Spectral Analysis to Nonstationary Data
. (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/12584
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):
Rahim, Karim. “Applications of Multitaper Spectral Analysis to Nonstationary Data
.” 2014. Thesis, Queens University. Accessed February 27, 2021.
http://hdl.handle.net/1974/12584.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Rahim, Karim. “Applications of Multitaper Spectral Analysis to Nonstationary Data
.” 2014. Web. 27 Feb 2021.
Vancouver:
Rahim K. Applications of Multitaper Spectral Analysis to Nonstationary Data
. [Internet] [Thesis]. Queens University; 2014. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1974/12584.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Rahim K. Applications of Multitaper Spectral Analysis to Nonstationary Data
. [Thesis]. Queens University; 2014. Available from: http://hdl.handle.net/1974/12584
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Johannesburg
14.
Human, Johannes Urbanus.
Some aspects of harmonic time series analysis.
Degree: PhD, 2012, University of Johannesburg
URL: http://hdl.handle.net/10210/4275
► Harmonic time series are often used to describe the periodic nature of a time series, for example the periodic nature of a variable star’s observed…
(more)
▼ Harmonic time series are often used to describe the periodic nature of a time series, for example the periodic nature of a variable star’s observed light curve. Statistical methods for determining the number of harmonic components to include in harmonic time series are limited. In this thesis a stepwise bootstrap procedure based on a F-type statistic is suggested. The performance of the stepwise procedure is compared to that of Schwartz’s Bayesian Criterion (SBC) and a procedure based on a statistic described by Siegel (1980). Harmonic series with correlated noise terms and irregularly spaced observations are also considered. Tests to detect changes in harmonic parameters are also derived in this thesis. A cumulative sum statistic to test for constant amplitude is derived. It is shown that testing for constant amplitude is equivalent to testing for constant slope in simple linear regression. We also derive a likelihood ratio statistic to test for constant amplitude. It is shown that the latter likelihood ratio statistic is asymptotically equivalent to the cumulative sum statistic. These statistics are compared to a quadratic form statistic used by Koen (2009). Likelihood ratio tests are also derived for detecting changes in the frequency or phase of harmonic time series. Graphical devices to aid in diagnostic checking are suggested.
Subjects/Keywords: Harmonic analysis; Time-series analysis
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Manager
APA (6th Edition):
Human, J. U. (2012). Some aspects of harmonic time series analysis. (Doctoral Dissertation). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/4275
Chicago Manual of Style (16th Edition):
Human, Johannes Urbanus. “Some aspects of harmonic time series analysis.” 2012. Doctoral Dissertation, University of Johannesburg. Accessed February 27, 2021.
http://hdl.handle.net/10210/4275.
MLA Handbook (7th Edition):
Human, Johannes Urbanus. “Some aspects of harmonic time series analysis.” 2012. Web. 27 Feb 2021.
Vancouver:
Human JU. Some aspects of harmonic time series analysis. [Internet] [Doctoral dissertation]. University of Johannesburg; 2012. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/10210/4275.
Council of Science Editors:
Human JU. Some aspects of harmonic time series analysis. [Doctoral Dissertation]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/4275
Addis Ababa University
15.
Tewodros, Gebru.
The Determinants of Economic Growth in Ethiopia: A Time Series Analysis
.
Degree: 2015, Addis Ababa University
URL: http://etd.aau.edu.et/dspace/handle/123456789/6821
► The main objective of this study is to investigate the determinants of economic growth in Ethiopia during the period 1974-2013. The Autoregressive Distributed Lag (ARDL)…
(more)
▼ The main objective of this study is to investigate the determinants of economic growth in
Ethiopia during the period 1974-2013. The Autoregressive Distributed Lag (ARDL) Approach to
Co-integration and Error Correction Model are applied in order to investig ate the long-run and
short run relationship between the dependent variable (real GDP) and its determinants. The
finding of the Bounds test shows that there is a stable long run relationship between real GDP,
Physical capital, human capital, export, aid, external debt and inflation.
The empirical results reveal that both physical capital and human capital are found to have
positive impact on economic growth while debt affects economic growth negatively and statically
significant at 1 percent. However, the study found out that export of goods and service, foreign
aid and inflation have statistically insignificant impact on economic growth in the long run. This
study has also an important policy implication. The findings of this study imply that economic
growth can be improved significantly when the physical capital and human capital increases.
Hence policy makers and /or the government should strive to increase capital formation
(investment) which is believed as a back bone of growth and has allocate adequate finance for
human capital, which will help to work on quality of education and providing basic health
services to the society. In addition to its effort, there should be a close monitoring and consistent
debt management strategies, which is used to avoid misallocation and mismanagement of
external debt problem.
Advisors/Committee Members: Dr. Fantu Guta (advisor).
Subjects/Keywords: Economic Growth;
Time Series
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Manager
APA (6th Edition):
Tewodros, G. (2015). The Determinants of Economic Growth in Ethiopia: A Time Series Analysis
. (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/6821
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):
Tewodros, Gebru. “The Determinants of Economic Growth in Ethiopia: A Time Series Analysis
.” 2015. Thesis, Addis Ababa University. Accessed February 27, 2021.
http://etd.aau.edu.et/dspace/handle/123456789/6821.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Tewodros, Gebru. “The Determinants of Economic Growth in Ethiopia: A Time Series Analysis
.” 2015. Web. 27 Feb 2021.
Vancouver:
Tewodros G. The Determinants of Economic Growth in Ethiopia: A Time Series Analysis
. [Internet] [Thesis]. Addis Ababa University; 2015. [cited 2021 Feb 27].
Available from: http://etd.aau.edu.et/dspace/handle/123456789/6821.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Tewodros G. The Determinants of Economic Growth in Ethiopia: A Time Series Analysis
. [Thesis]. Addis Ababa University; 2015. Available from: http://etd.aau.edu.et/dspace/handle/123456789/6821
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
NSYSU
16.
Kau, Wei-Hao.
Time series prediction using LSTM Network Models.
Degree: Master, Applied Mathematics, 2018, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612118-160809
► As recent computing hardware technology has undergone rapid and significant advances, complex methods that require a lot of computing power have been realized, which has…
(more)
▼ As recent computing hardware technology has undergone rapid and significant advances, complex methods that require a lot of computing power have been realized, which has led to the development of more machine learning methods and neural network models. This paper discusses the Long short-term memory (LSTM) network model of recurrent neural networks. The first part of this paper introduces the basic concept of LSTM and its training method. The second part discusses short- and long-term prediction, and compares their differences with the conventional
time series model. The third part compares the prediction performance of the conventional
time series model and LSTM by analysing simulated data. In the empirical study, a Long short-term memory network model is fitted for bicycle rental data in Kaohsiung, and predictive analysis is performed.
Advisors/Committee Members: Mong-Na Lo Huang (chair), Mei-Hui Guo (committee member), Chung Chang (chair), Huang, Shih-Feng (chair), Liang-Ching Lin (chair).
Subjects/Keywords: prediction; LSTM; time series model
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APA ·
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Kau, W. (2018). Time series prediction using LSTM Network Models. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612118-160809
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):
Kau, Wei-Hao. “Time series prediction using LSTM Network Models.” 2018. Thesis, NSYSU. Accessed February 27, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612118-160809.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Kau, Wei-Hao. “Time series prediction using LSTM Network Models.” 2018. Web. 27 Feb 2021.
Vancouver:
Kau W. Time series prediction using LSTM Network Models. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Feb 27].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612118-160809.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Kau W. Time series prediction using LSTM Network Models. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612118-160809
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
UCLA
17.
Meade, Christopher.
Improving Automated Time Series Forecasting with the use of Model Ensembles.
Degree: Statistics, 2019, UCLA
URL: http://www.escholarship.org/uc/item/91q598s7
► There currently exist several “black box” software libraries for the automatic forecasting of time series. Popular among these are the 'forecast' and 'bsts' packages for…
(more)
▼ There currently exist several “black box” software libraries for the automatic forecasting of time series. Popular among these are the 'forecast' and 'bsts' packages for R, which havefunctions to automatically fit several common classes of time series models, such as theautoregressive integrated moving average (ARIMA) and the family of exponential smoothingmodels, among others. It is often the case that what one gains from the ease in fitting theseautomatic methods comes at the cost of predictive performance. In this paper, we proposeseveral methods to improve the prediction accuracy of automatic time series forecasting, all ofwhich relate to creating ensembles of models automatically fit from these packages. Weexplore different ways that one can construct these ensembles and evaluate each on abenchmark time series dataset. In addition, we provide the R code used to construct these ensembles.
Subjects/Keywords: Statistics; ensembles; forecasting; time series
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APA ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Meade, C. (2019). Improving Automated Time Series Forecasting with the use of Model Ensembles. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/91q598s7
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):
Meade, Christopher. “Improving Automated Time Series Forecasting with the use of Model Ensembles.” 2019. Thesis, UCLA. Accessed February 27, 2021.
http://www.escholarship.org/uc/item/91q598s7.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Meade, Christopher. “Improving Automated Time Series Forecasting with the use of Model Ensembles.” 2019. Web. 27 Feb 2021.
Vancouver:
Meade C. Improving Automated Time Series Forecasting with the use of Model Ensembles. [Internet] [Thesis]. UCLA; 2019. [cited 2021 Feb 27].
Available from: http://www.escholarship.org/uc/item/91q598s7.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Meade C. Improving Automated Time Series Forecasting with the use of Model Ensembles. [Thesis]. UCLA; 2019. Available from: http://www.escholarship.org/uc/item/91q598s7
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Illinois – Chicago
18.
Amornbunchornvej, Chainarong.
Inference of Leadership of Coordinated Activity in Time Series.
Degree: 2018, University of Illinois – Chicago
URL: http://hdl.handle.net/10027/23252
► When a group of people decides to move somewhere together, who is the initiator who starts moving and everyone follows? Do the group members follow…
(more)
▼ When a group of people decides to move somewhere together, who is the initiator who starts moving and everyone follows? Do the group members follow friends around them or do they prefer to follow specific individuals? These questions are about leadership. Leadership plays a key role in social animals', including humans', decision-making and coalescence in coordinated activities such as hunting, migration, sport, diplomatic negotiation, etc. In these coordinated activities, leadership is a process which organizes interactions among members to make a group achieve collective goals. Understanding initiation of coordinated activities allows scientists to gain more insight into social species' behaviors. However, by using only the data on
time series of activities, inferring leadership, as manifested by the initiation of coordinated activities, faces many challenging issues. First, there is no fundamental concept to describe these activities computationally. Second, coordinated activities are dynamic. Third, several different coordinated activities may occur simultaneously among subgroups. To fill these remaining gaps in leadership inference, we formalize several computational leadership problems and propose methodologies to solve them.
We evaluate and demonstrate the performance of the proposed frameworks in both simulated and real-world datasets, such as baboon trajectories,
time series of fish movement as well as
time series of closing price of stock market. The frameworks perform better than non-trivial baselines in both simulated and real-world datasets. Our problem formalization and frameworks enable opportunities for scientists to analyze coordinated activities and generate scientific hypotheses about collective behaviors that can be tested statistically and in the field.
Advisors/Committee Members: Berger-Wolf, Tanya Y. (advisor), Zheleva, Elena (committee member), Ziebart, Brian (committee member), Turan, Gyorgy (committee member), Keogh, Eamonn (committee member), Berger-Wolf, Tanya Y. (chair).
Subjects/Keywords: Leadership; Coordination; Time series; Inference
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Manager
APA (6th Edition):
Amornbunchornvej, C. (2018). Inference of Leadership of Coordinated Activity in Time Series. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/23252
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):
Amornbunchornvej, Chainarong. “Inference of Leadership of Coordinated Activity in Time Series.” 2018. Thesis, University of Illinois – Chicago. Accessed February 27, 2021.
http://hdl.handle.net/10027/23252.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Amornbunchornvej, Chainarong. “Inference of Leadership of Coordinated Activity in Time Series.” 2018. Web. 27 Feb 2021.
Vancouver:
Amornbunchornvej C. Inference of Leadership of Coordinated Activity in Time Series. [Internet] [Thesis]. University of Illinois – Chicago; 2018. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/10027/23252.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Amornbunchornvej C. Inference of Leadership of Coordinated Activity in Time Series. [Thesis]. University of Illinois – Chicago; 2018. Available from: http://hdl.handle.net/10027/23252
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Houston
19.
Biolsi, Christopher.
Essays on State Dependence in the Government Spending Multiplier.
Degree: PhD, Economics, 2015, University of Houston
URL: http://hdl.handle.net/10657/5463
► This dissertation is comprises three essays. The first attempts to answer the following question. Is fiscal policy more effective, as measured by the government spending…
(more)
▼ This dissertation is comprises three essays. The first attempts to answer the following question. Is fiscal policy more effective, as measured by the government spending multiplier, when the economy is “weak” relative to when it is “strong?” Results in the empirical literature have been mixed on this question. I use local projection techniques to estimate the impulse response functions of real output and real government spending to a shock to military spending. In addition, I attempt to endogenously estimate the level of the unemployment rate that distinguishes between states of the economy. I find that fiscal multipliers are near two at horizons of two to four years when unemployment is relatively high, compared to below 1 when unemployment is low. The second paper seeks to understand why disagreement in the emprical literature is so pervasive and if there are certain modeling choices that systematically lead to particular findings on the state dependence of the government spending multiplier. I identify eight dimensions along which many of the studies in the literature vary and determine if choices along these dimensions have a systematic impact on the results. I conclude that estimation of a state-dependent multiplier is, in general, not robust to various plausible specification assumptions. Finally, I estimate the effect of government spending at the county level using a previously little studied spending program, the Vinson-Trammell Act of 1934. Stimulated by fears about Japanese military expansion, this act aimed to build up the United States Navy to treaty allowances. I am able to identify local areas in the United States that hosted shipyards in 1934, and I estimate the effects of government spending on these areas. I find that manufacturing output, employment, and earnings all rise faster over the course of the 1930s in counties hosting shipyards at the
time of the bill’s passage. Also, I see significantly faster growth in county level retail sales and a positive effect on household consumption. Attempting to scale these results to an aggregate government spending multiplier, however, leads to a wide range of estimates for the effect on overall output.
Advisors/Committee Members: Sorensen, Bent E. (advisor), Papell, David H. (advisor), Craig, Steven Gael (committee member), Susmel, Raul (committee member).
Subjects/Keywords: Fiscal Policy; Time series
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APA (6th Edition):
Biolsi, C. (2015). Essays on State Dependence in the Government Spending Multiplier. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/5463
Chicago Manual of Style (16th Edition):
Biolsi, Christopher. “Essays on State Dependence in the Government Spending Multiplier.” 2015. Doctoral Dissertation, University of Houston. Accessed February 27, 2021.
http://hdl.handle.net/10657/5463.
MLA Handbook (7th Edition):
Biolsi, Christopher. “Essays on State Dependence in the Government Spending Multiplier.” 2015. Web. 27 Feb 2021.
Vancouver:
Biolsi C. Essays on State Dependence in the Government Spending Multiplier. [Internet] [Doctoral dissertation]. University of Houston; 2015. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/10657/5463.
Council of Science Editors:
Biolsi C. Essays on State Dependence in the Government Spending Multiplier. [Doctoral Dissertation]. University of Houston; 2015. Available from: http://hdl.handle.net/10657/5463
University of Leicester
20.
Boonyasana, Kwanruetai.
World electricity co-operation.
Degree: PhD, 2013, University of Leicester
URL: https://figshare.com/articles/World_electricity_co-operation/10147556
;
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.568180
► This thesis evaluates the effect of electricity co-operation regarding import and export on electricity prices for OECD countries and on CO2 emissions for the world.…
(more)
▼ This thesis evaluates the effect of electricity co-operation regarding import and export on electricity prices for OECD countries and on CO2 emissions for the world. In addition, the study investigates which kinds of renewable energies provide the best economic future for Canada and the U.S. There are three main sections to the thesis. Firstly, panel data analysis determines the electricity price functions, using 29 OECD countries’ yearly data from 1980 to 2007. Membership of the European Union, used to investigate effect of high level co-operation on price, is seen to decrease household and industry prices, but is not significant for household price. The effect of electricity trading in OECD countries is not found to deliver cheaper electricity suggesting that these countries need to co-operate more closely to increase competition and improve efficiency in electricity markets. Secondly, panel data analysis determines parameters of the CO2 emissions function, using 131 countries’ yearly data from 1971 to 2007. The world results show that electricity co-operation is highly significant in decreasing CO2 emissions per unit of generation, thus supporting the hypothesis. At the continent level, Asia shows the highest CO2 decrease from electricity import, with the lowest decrease being for Africa. Electricity export for North America, Latin America and Europe is found to be highly significant in decreasing CO2 emissions. Finally, time series analysis of yearly data for Canada and the U.S. from 1978 to 2009 is used to determine the electricity price functions. For Canada, electricity import is found to be highly significant in decreasing household electricity price, but not so for the U.S. Renewable energies such as wind and hydro are seen to be the future of electricity generation for Canada, but the results for the U.S. indicate that no type of renewable energy can reduce electricity price.
Subjects/Keywords: 333.793; panel data; time series
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APA (6th Edition):
Boonyasana, K. (2013). World electricity co-operation. (Doctoral Dissertation). University of Leicester. Retrieved from https://figshare.com/articles/World_electricity_co-operation/10147556 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.568180
Chicago Manual of Style (16th Edition):
Boonyasana, Kwanruetai. “World electricity co-operation.” 2013. Doctoral Dissertation, University of Leicester. Accessed February 27, 2021.
https://figshare.com/articles/World_electricity_co-operation/10147556 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.568180.
MLA Handbook (7th Edition):
Boonyasana, Kwanruetai. “World electricity co-operation.” 2013. Web. 27 Feb 2021.
Vancouver:
Boonyasana K. World electricity co-operation. [Internet] [Doctoral dissertation]. University of Leicester; 2013. [cited 2021 Feb 27].
Available from: https://figshare.com/articles/World_electricity_co-operation/10147556 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.568180.
Council of Science Editors:
Boonyasana K. World electricity co-operation. [Doctoral Dissertation]. University of Leicester; 2013. Available from: https://figshare.com/articles/World_electricity_co-operation/10147556 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.568180
Hong Kong University of Science and Technology
21.
Wu, Degang.
Coupling analysis in time series using information theory and dynamical systems theory.
Degree: 2016, Hong Kong University of Science and Technology
URL: http://repository.ust.hk/ir/Record/1783.1-87522
;
https://doi.org/10.14711/thesis-b1736171
;
http://repository.ust.hk/ir/bitstream/1783.1-87522/1/th_redirect.html
► Inferring causality from observations of different entities is central to science. Time series is an important form of observations in subjects ranging from physics, geology…
(more)
▼ Inferring causality from observations of different entities is central to science. Time series is an important form of observations in subjects ranging from physics, geology and medicine to finance. Although non-experimental observations such as time series measured from geological entities and financial markets are in general never sufficient for causality inference in the strictest sense, couplings inferred from non-experimental time series are still strong hints for causality. Linear methods such as Granger causality, and nonlinear methods such as transfer entropy, have been developed for coupling inference in binary time series or even multiple time series. Among nonlinear method, there are methods such as Cross Convergent Mapping (CCM) which assumes the process under investigation is deterministic and methods such as transfer entropy in principle can accommodate stochastic processes. In this work, we combine CCM and Holstein’s embedding criterion, a criterion based on information entropy, to create an algorithm that is more sensitive than CCM.
Subjects/Keywords: Time-series analysis
; Mathematical models
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Manager
APA (6th Edition):
Wu, D. (2016). Coupling analysis in time series using information theory and dynamical systems theory. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-87522 ; https://doi.org/10.14711/thesis-b1736171 ; http://repository.ust.hk/ir/bitstream/1783.1-87522/1/th_redirect.html
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):
Wu, Degang. “Coupling analysis in time series using information theory and dynamical systems theory.” 2016. Thesis, Hong Kong University of Science and Technology. Accessed February 27, 2021.
http://repository.ust.hk/ir/Record/1783.1-87522 ; https://doi.org/10.14711/thesis-b1736171 ; http://repository.ust.hk/ir/bitstream/1783.1-87522/1/th_redirect.html.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Wu, Degang. “Coupling analysis in time series using information theory and dynamical systems theory.” 2016. Web. 27 Feb 2021.
Vancouver:
Wu D. Coupling analysis in time series using information theory and dynamical systems theory. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2016. [cited 2021 Feb 27].
Available from: http://repository.ust.hk/ir/Record/1783.1-87522 ; https://doi.org/10.14711/thesis-b1736171 ; http://repository.ust.hk/ir/bitstream/1783.1-87522/1/th_redirect.html.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Wu D. Coupling analysis in time series using information theory and dynamical systems theory. [Thesis]. Hong Kong University of Science and Technology; 2016. Available from: http://repository.ust.hk/ir/Record/1783.1-87522 ; https://doi.org/10.14711/thesis-b1736171 ; http://repository.ust.hk/ir/bitstream/1783.1-87522/1/th_redirect.html
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Delft University of Technology
22.
Klop, Stijn (author).
From observation well to model area: Estimating groundwater levels spatially using time series analysis.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:362f6b0f-b3aa-41c6-b47e-b625c963d8a0
► Estimating groundwater levels spatially using time series analysis. With time series analysis a response function of an observation well is determined. The response function is…
(more)
▼ Estimating groundwater levels spatially using time series analysis. With time series analysis a response function of an observation well is determined. The response function is used to calibrate a conceptual groundwater model. This conceptual model is used to estimate groundwater levels in an area.
Water Management
Advisors/Committee Members: Bakker, Mark (mentor), Schoups, Gerrit (graduation committee), Tiberius, Christiaan (graduation committee), Schaars, Frans (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: Groundwater; time series analysis
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APA (6th Edition):
Klop, S. (. (2019). From observation well to model area: Estimating groundwater levels spatially using time series analysis. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:362f6b0f-b3aa-41c6-b47e-b625c963d8a0
Chicago Manual of Style (16th Edition):
Klop, Stijn (author). “From observation well to model area: Estimating groundwater levels spatially using time series analysis.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021.
http://resolver.tudelft.nl/uuid:362f6b0f-b3aa-41c6-b47e-b625c963d8a0.
MLA Handbook (7th Edition):
Klop, Stijn (author). “From observation well to model area: Estimating groundwater levels spatially using time series analysis.” 2019. Web. 27 Feb 2021.
Vancouver:
Klop S(. From observation well to model area: Estimating groundwater levels spatially using time series analysis. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27].
Available from: http://resolver.tudelft.nl/uuid:362f6b0f-b3aa-41c6-b47e-b625c963d8a0.
Council of Science Editors:
Klop S(. From observation well to model area: Estimating groundwater levels spatially using time series analysis. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:362f6b0f-b3aa-41c6-b47e-b625c963d8a0
University of Florida
23.
Ghosh, Satyajit.
Bayesian Estimation and Model Selection Consistency of High Dimensional Time Series.
Degree: PhD, Statistics, 2018, University of Florida
URL: https://ufdc.ufl.edu/UFE0052567
Vector autoregressive (VAR) models aim to capture linear temporal interdependencies amongst multiple time series. They have been widely used in macroeconomics and financial econometrics and more recently have found novel applications in
Advisors/Committee Members: KHARE,KSHITIJ (committee chair), GHOSH,MALAY (committee member), HUO,ZHIGUANG (committee member).Subjects/Keywords: bayesian – high-dimension – time-series
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to Zotero / EndNote / Reference
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APA (6th Edition):
Ghosh, S. (2018). Bayesian Estimation and Model Selection Consistency of High Dimensional Time Series. (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0052567
Chicago Manual of Style (16th Edition):
Ghosh, Satyajit. “Bayesian Estimation and Model Selection Consistency of High Dimensional Time Series.” 2018. Doctoral Dissertation, University of Florida. Accessed February 27, 2021.
https://ufdc.ufl.edu/UFE0052567.
MLA Handbook (7th Edition):
Ghosh, Satyajit. “Bayesian Estimation and Model Selection Consistency of High Dimensional Time Series.” 2018. Web. 27 Feb 2021.
Vancouver:
Ghosh S. Bayesian Estimation and Model Selection Consistency of High Dimensional Time Series. [Internet] [Doctoral dissertation]. University of Florida; 2018. [cited 2021 Feb 27].
Available from: https://ufdc.ufl.edu/UFE0052567.
Council of Science Editors:
Ghosh S. Bayesian Estimation and Model Selection Consistency of High Dimensional Time Series. [Doctoral Dissertation]. University of Florida; 2018. Available from: https://ufdc.ufl.edu/UFE0052567
University of Toronto
24.
Karapanagiotidis, Paul.
Essays in Financial and Macro Econometrics.
Degree: PhD, 2014, University of Toronto
URL: http://hdl.handle.net/1807/68202
► Theory suggests that physical commodity prices may exhibit nonlinear features such as bubbles and various types of asymmetries. Chapter one investigates these claims empirically by…
(more)
▼ Theory suggests that physical commodity prices may exhibit nonlinear features such as bubbles and various types of asymmetries. Chapter one investigates these claims empirically by introducing a new
time series model apt to capture such features. The data set is composed of 25 individual, continuous contract, commodity futures price
series, representative of a number of industry sectors including softs, precious metals, energy, and livestock. It is shown that the linear causal ARMA model with Gaussian innovations is unable to adequately account for the features of the data. In the purely descriptive
time series literature, often a threshold autoregression (TAR) is employed to model cycles or asymmetries. Rather than take this approach, we suggest a novel process which is able to accommodate both bubbles and asymmetries in a flexible way. This process is composed of both causal and noncausal components and is formalized as the mixed causal/noncausal autoregressive model of order (r; s). Estimating the mixed causal/noncausal model with leptokurtic errors, by an approximated maximum likelihood method, results in dramatically improved model fit according to the Akaike information criterion. Comparisons of the estimated unconditional distributions of both the purely causal and mixed models also suggest that the mixed causal/noncausal model is more representative of the data according to the Kullback-Leibler measure. Moreover, these estimation results demonstrate that allowing for such leptokurtic errors permits identification of various types of asymmetries. Finally, a strategy for computing the multiple steps ahead forecast of the conditional distribution is discussed.Chapter two considers a vector autoregressive model (VAR) model with stochastic volatility which appeals to the Inverse Wishart distribution. Dramatic changes in macroeconomic
time series volatility pose a challenge to contemporary VAR forecasting models. Traditionally, the conditional volatility of such models had been assumed constant over
time or allowed for breaks across long
time periods. More recent work, however, has improved forecasts by allowing the conditional volatility to be completely
time variant by specifying the VAR innovation variance as a distinct discrete
time process. For example, Clark (2011) specifies the elements of the covariance matrix process of the VAR innovations as linear functions of independent nonstationary processes. Unfortunately, there is no empirical reason to believe that the VAR innovation volatility processes of macroeconomic growth
series are nonstationary, nor that the volatility dynamics of each
series are structured in this way. This suggests that a more robust specification on the volatility process – one that both easily captures volatility spill-over across
time series and exhibits stationary behaviour – should improve density forecasts, especially over the long-run forecasting horizon. In this respect, we employ a latent Inverse Wishart autoregressive stochastic volatility specification on the conditional…
Advisors/Committee Members: Christian, Gourieroux, Economics.
Subjects/Keywords: Econometrics; Time series; 0501
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APA (6th Edition):
Karapanagiotidis, P. (2014). Essays in Financial and Macro Econometrics. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/68202
Chicago Manual of Style (16th Edition):
Karapanagiotidis, Paul. “Essays in Financial and Macro Econometrics.” 2014. Doctoral Dissertation, University of Toronto. Accessed February 27, 2021.
http://hdl.handle.net/1807/68202.
MLA Handbook (7th Edition):
Karapanagiotidis, Paul. “Essays in Financial and Macro Econometrics.” 2014. Web. 27 Feb 2021.
Vancouver:
Karapanagiotidis P. Essays in Financial and Macro Econometrics. [Internet] [Doctoral dissertation]. University of Toronto; 2014. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/1807/68202.
Council of Science Editors:
Karapanagiotidis P. Essays in Financial and Macro Econometrics. [Doctoral Dissertation]. University of Toronto; 2014. Available from: http://hdl.handle.net/1807/68202
University of Illinois – Urbana-Champaign
25.
Zwilling, Christopher Eric.
New approaches for outlier detection.
Degree: PhD, Psychology, 2016, University of Illinois – Urbana-Champaign
URL: http://hdl.handle.net/2142/97645
► Outlier detection has relevance in many modern day contexts, including health care, engineering, data processing and analysis, credit card fraud, monitoring computer and internet intrusions…
(more)
▼ Outlier detection has relevance in many modern day contexts, including health care, engineering, data processing and analysis, credit card fraud, monitoring computer and internet intrusions and wearable personal health sensors. Outlier detection once represented a single pre-processing step, completed prior to the analysis of data proper. Today it has importance in all stages of the data analysis pipeline, from initial processing to defining data points of interest, such as when a sensor detects an anomaly. Moreover, as data sets have grown to encompass millions and billions of observations and variables, it is imperative to have outlier detection methods capable of effectively and automatically winnowing through large amounts of data with few or no inputs from a data analyst. Many existing outlier detection methods are constrained in certain ways which might limit their utility and efficacy. For instance, it is not uncommon for outlier detection methods to require some knowledge about the data under study or require the analyst to specify information about the number of outliers in the data. Another possible constraint of many outlier detection methods is the use of the raw data. Sometimes outliers can readily be detected in the raw data; but sometimes not, in which case one can achieve greater sensitivity and accuracy from features derived from data. This study uses feature extraction on multivariate
time series data and demonstrates the efficacy of a set of features and their potential for aggregation through the use of Voronoi diagrams. Voronoi diagrams are constructed from the data to create tessellations which satisfy certain geometric properties. The covariance based outlier detection is proposed and demonstrated to addresses both of these challenges. It utilizes covariance information in the data and its efficacy lies in its ability to take a set of features constructed from the data and determine which feature is best at detecting outliers. The method is shown to work effectively on
time series data; but it is general and can be applied or extended to other types of data objects and data sets.
Advisors/Committee Members: Wang, Michelle Y. (advisor), Wang, Michelle Y. (Committee Chair), Anderson, Carolyn (committee member), Kohn, Hans-Friedrich (committee member), Marden, John (committee member), Drasgow, Fritz (committee member).
Subjects/Keywords: Outliers; Covariance; Time series
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Zwilling, C. E. (2016). New approaches for outlier detection. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/97645
Chicago Manual of Style (16th Edition):
Zwilling, Christopher Eric. “New approaches for outlier detection.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed February 27, 2021.
http://hdl.handle.net/2142/97645.
MLA Handbook (7th Edition):
Zwilling, Christopher Eric. “New approaches for outlier detection.” 2016. Web. 27 Feb 2021.
Vancouver:
Zwilling CE. New approaches for outlier detection. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/2142/97645.
Council of Science Editors:
Zwilling CE. New approaches for outlier detection. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/97645
University of Melbourne
26.
Xu, Zhenghua.
Online time series approximation and prediction.
Degree: 2012, University of Melbourne
URL: http://hdl.handle.net/11343/37329
► In recent years, there are rapidly increasing research interests in the management of time series data due to its importance in a variety of applications…
(more)
▼ In recent years, there are rapidly increasing research interests in the management of time series data due to its importance in a variety of applications such as network traffic management, telecommunications, finance, sensor network and location based services. In this thesis, we focus on two important problems of the management of time series data: the online time series approximation problem and the online time series prediction problem.
The time series approximation can reduce the space and the computational cost of storing and transmitting time series data, and also reduce the workload of the data processing. Segmentation is one of the most commonly used methods to meet this requirement. However, while most of the current segmentation methods aim to minimize the holistic error between the approximation and the original time series, few works try to represent time series as compact as possible with an error bound guarantee on each data point. Moreover, in many real world situations, the patterns of the time series do not follow a constant rule such that using only one type of functions may not yield the best compaction.
Motivated by these observations, we propose an online segmentation algorithm which approximates time series by a set of different types of candidate functions (poly nomials of different orders, exponential functions, etc.) and adaptively chooses the most compact one as the pattern of the time series changes. A challenge in this approach is to determine the approximation function on the fly (“online”). Thereby, we further present a novel method to efficiently generate the compact approximation of a time series in an online fashion for several types of candidate functions. This method incrementally narrows the feasible coefficient spaces of candidate functions in coefficient coordinate systems such that it can make each segment as long as possible given an error bound on each data point. Extensive experimental results show that our algorithm generates more compact approximations of the time series with lower average errors than the state-of-the-art algorithm.
The time series prediction aims to predict future values of the time series according to their previously observed values. In this thesis, we focus our work on a specific branch of the time series prediction: the online locational time series prediction problem, i.e, predicting the final locations of the locational time series according to their current observed locational time series values on the fly. This problem is also called the destination prediction problem and the systems used to solve this problem are the called destination prediction systems. However, most of current destination prediction systems are based on the traveling histories of specific users so they are too ad hoc to accurately predict other users’ destination. In our work, we propose the first generic destination prediction solution to…
Subjects/Keywords: time series; approximation; prediction
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Xu, Z. (2012). Online time series approximation and prediction. (Masters Thesis). University of Melbourne. Retrieved from http://hdl.handle.net/11343/37329
Chicago Manual of Style (16th Edition):
Xu, Zhenghua. “Online time series approximation and prediction.” 2012. Masters Thesis, University of Melbourne. Accessed February 27, 2021.
http://hdl.handle.net/11343/37329.
MLA Handbook (7th Edition):
Xu, Zhenghua. “Online time series approximation and prediction.” 2012. Web. 27 Feb 2021.
Vancouver:
Xu Z. Online time series approximation and prediction. [Internet] [Masters thesis]. University of Melbourne; 2012. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/11343/37329.
Council of Science Editors:
Xu Z. Online time series approximation and prediction. [Masters Thesis]. University of Melbourne; 2012. Available from: http://hdl.handle.net/11343/37329
University of Sydney
27.
Wang, Zheng.
Solar Power Forecasting
.
Degree: 2019, University of Sydney
URL: http://hdl.handle.net/2123/21248
► Solar energy is a promising environmentally-friendly energy source. Yet its variability affects negatively the large-scale integration into the electricity grid and therefore accurate forecasting of…
(more)
▼ Solar energy is a promising environmentally-friendly energy source. Yet its variability affects negatively the large-scale integration into the electricity grid and therefore accurate forecasting of the power generated by PV systems is needed. The objective of this thesis is to explore the possibility of using machine learning methods to accurately predict solar power. We first explored the potential of instance-based methods and proposed two new methods: the data source weighted nearest neighbour (DWkNN) and the extended Pattern Sequence Forecasting (PSF) algorithms. DWkNN uses multiple data sources and considers their importance by learning the best weights based on previous data. PSF1 and PSF2 extended the standard PSF algorithm deal with data from multiple related time series. Then, we proposed two clustering-based methods for PV power prediction: direct and pair patterns. We used clustering to partition the days into groups with similar weather characteristics and then created a separate PV power prediction model for each group. The direct clustering groups the days based on their weather profiles, while the pair patterns consider the weather type transition between two consecutive days. We also investigated ensemble methods and proposed static and dynamic ensembles of neural networks. We first proposed three strategies for creating static ensembles based on random example and feature sampling, as well as four strategies for creating dynamic ensembles by adaptively updating the weights of the ensemble members based on past performance. We then explored the use of meta-learning to further improve the performance of the dynamic ensembles. The methods proposed in this thesis can be used by PV plant and electricity market operators for decision making, improving the utilisation of the generated PV power, planning maintenance and also facilitating the large-scale integration of PV power in the electricity grid.
Subjects/Keywords: Solar;
Power;
Time;
Series;
Forecast
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APA (6th Edition):
Wang, Z. (2019). Solar Power Forecasting
. (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/21248
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, Zheng. “Solar Power Forecasting
.” 2019. Thesis, University of Sydney. Accessed February 27, 2021.
http://hdl.handle.net/2123/21248.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Wang, Zheng. “Solar Power Forecasting
.” 2019. Web. 27 Feb 2021.
Vancouver:
Wang Z. Solar Power Forecasting
. [Internet] [Thesis]. University of Sydney; 2019. [cited 2021 Feb 27].
Available from: http://hdl.handle.net/2123/21248.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Wang Z. Solar Power Forecasting
. [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/21248
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Rutgers University
28.
Liu, Xialu, 1986-.
New models and methods for time series analysis in big data era.
Degree: PhD, Statistics and Biostatistics, 2015, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/47468/
► In big data era, available information becomes massive and complex and is often observed over time. Conventional time series models are limited in capability of…
(more)
▼ In big data era, available information becomes massive and complex and is often observed over time. Conventional time series models are limited in capability of dealing with these type of data. This dissertation focuses on developing new statistical models, along with their associated estimation procedures, to analyze time series data in functional form, and in high dimension, with linear or nonlinear dynamics, which can be broadly applicable to finance, environment, engineering, biological and medical sciences. Functional data analysis has became an increasingly popular class of problems in statistical research. However, functional data observed over time with serial dependence remains a less studied area. Motivated by Bosq (2000), who worst introduced the functional autoregressive (FAR) models, we propose a convolutional functional autoregressive (CFAR) model, where the function at time t is a result of the sum of convolutions of the past functions with a set of convolution functions, plus a noise process, mimicking the autoregressive process. It provides an intuitive and direct interpretation of the dynamics of a stochastic process. We adopt a sieve estimation procedure based on the B-spline approximation of the convolution functions. We establish convergence rate of the proposed estimator, and investigate its theoretical properties. The model building, model validation, and prediction procedures are also developed. As for high-dimensional time series data, dimension reduction is an important issue and can be effectively performed by factor analysis. Considering the factor impacts may vary under different conditions, we propose a factor model with regime-switching mechanism, allowing loadings to change across regimes, and combined eigendecomposition and Viterbi algorithm for estimation. We discover that, with multiple states of different 'strength', the convergence rate of loading matrix estimator for strong states is the same as the one-regime case, while the rate improves for weak states, gaining extra information from strong states. The theoretical properties of the procedure are investigated as well. In addition, we propose a new class of nonparametric seasonal time series models under the framework of the functional coefficient model. The coefficients in the proposed model change over time and consist of the trend and seasonal components to characterize seasonality. A local linear approach is developed to estimate the nonparametric trend and seasonal effect functions. The proposed methodologies are illustrated by two simulated examples and the model is applied to characterizing the seasonality of the monthly number of tourists visiting Hawaii.
Advisors/Committee Members: Chen, Rong (chair), Xiao, Han (internal member), Dicker, Lee (internal member), Lin, Xiaodong (outside member).
Subjects/Keywords: Time-series analysis; Big data
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APA (6th Edition):
Liu, Xialu, 1. (2015). New models and methods for time series analysis in big data era. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/47468/
Chicago Manual of Style (16th Edition):
Liu, Xialu, 1986-. “New models and methods for time series analysis in big data era.” 2015. Doctoral Dissertation, Rutgers University. Accessed February 27, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/47468/.
MLA Handbook (7th Edition):
Liu, Xialu, 1986-. “New models and methods for time series analysis in big data era.” 2015. Web. 27 Feb 2021.
Vancouver:
Liu, Xialu 1. New models and methods for time series analysis in big data era. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2021 Feb 27].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47468/.
Council of Science Editors:
Liu, Xialu 1. New models and methods for time series analysis in big data era. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/47468/
Rutgers University
29.
Chang, Kun.
Topics in compositional, seasonal and spatial-temporal time series.
Degree: PhD, Statistics and Biostatistics, 2015, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/48411/
► This dissertation studies several topics in time series modeling. The discussion on seasonal time series, compositional time series and spatial-temporal time series brings new insight…
(more)
▼ This dissertation studies several topics in time series modeling. The discussion on seasonal time series, compositional time series and spatial-temporal time series brings new insight to the existing methods. Innovative methodologies are developed for modeling and forecasting purposes. These topics are not isolated but to naturally support each other under rigorous discussions. A variety of real examples are presented from economics, social science and geoscience areas. The second chapter introduces a new class of seasonal time series models, treating the seasonality as a stable composition through time. With the objective of forecasting the sum of the next ell observations, the concept of rolling season is adopted and a structure of rolling conditional distribution is formulated under the compositional time series framework. The probabilistic properties, the estimation and prediction, and the forecasting performance of the model are studied and demonstrated with simulation and real examples. The third chapter focuses on the discussion of compositional time series theories in multivariate models. It provides an idea to the modeling procedure of the multivariate time series that has sum constraints at each time. It also proposes a joint MLE method for threshold vector-error correction models. This chapter interprets the methodologies with an real example of the U.S. household consumption expenditures data. Threshold cointegration effects are analyzed on the U.S. real GDP growth rate. The estimation of TVECM is compared by the current two-step estimation method and the proposed joint MLE approach. Sensor allocation problem is studied in Chapter 4 under spatial-temporal models in Gaussian random fields. Given observations from existing sensors, the problem is solved by minimizing the integrated conditional variance based on different forecasting purposes. In this chapter, the time series are measured at different locations with both spatial and time series correlations. The spatial-temporal covariance structure is extensively discussed under both separable and nonseparable cases. The model is finally applied to the ozone level measurements in Harris County, Texas.
Advisors/Committee Members: Chen, Rong (chair), Xie, Minge (internal member), Xiao, Han (internal member), Cheng, Jerry (outside member).
Subjects/Keywords: Time-series analysis; Prediction theory
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Record Details
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
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Manager
APA (6th Edition):
Chang, K. (2015). Topics in compositional, seasonal and spatial-temporal time series. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/48411/
Chicago Manual of Style (16th Edition):
Chang, Kun. “Topics in compositional, seasonal and spatial-temporal time series.” 2015. Doctoral Dissertation, Rutgers University. Accessed February 27, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/48411/.
MLA Handbook (7th Edition):
Chang, Kun. “Topics in compositional, seasonal and spatial-temporal time series.” 2015. Web. 27 Feb 2021.
Vancouver:
Chang K. Topics in compositional, seasonal and spatial-temporal time series. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2021 Feb 27].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/48411/.
Council of Science Editors:
Chang K. Topics in compositional, seasonal and spatial-temporal time series. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/48411/
30.
Kwon, Joonsuk.
Three Essays on Multi-step forecasting with Partial Least Squares : Multi-step forecasting with Partial Least Squares.
Degree: Docteur es, Sciences économiques - EM2PSI, 2019, Cergy-Pontoise
URL: http://www.theses.fr/2019CERG1035
► Dans cette thèse, nous comparons les prévisions IMS, DMS et PLS à plusieurs horizons, en nous concentrant sur les propriétés combinatoires des PLS. Nous nous…
(more)
▼ Dans cette thèse, nous comparons les prévisions IMS, DMS et PLS à plusieurs horizons, en nous concentrant sur les propriétés combinatoires des PLS. Nous nous appuyons sur un article intéressant de Franses & Legerstee (2010), qui suggère comment la méthode dite des moindres carrés partiels (PLS) peut être considérée, dans le contexte de la prévision sur plusieurs étapes, comme une technique intermédiaire entre IMS et DMS. En fait, plutôt qu’un «intermédiaire», nous aimons considérer le PLS comme une forme de combinaison de IMS et de DMS.Cette thèse comprend quatre chapitres.Au chapitre 1, nous fournissons une revue de la littérature qui sert de contexte aux chapitres suivants. Ce chapitre sert de motivation pour les analyses ultérieures.Au chapitre 2, nous explorons les fonctionnalités de PLS considérées comme une combinaison d'IMS et de DMS. Nous étudions les propriétés de PLS en utilisant un algorithme suggéré par Garthwaite (1994).Nous étudions la relation entre IMS, DMS et PLS et comparons la précision de leurs prévisions à plusieurs horizons. Nous analysons les propriétés combinatoires de PLS dans la prévision en plusieurs étapes à l'aide d'un modèle simple AR (2). Pour comparer les performances de prévision, nous évaluons leurs propriétés asymptotiques sous des modèles bien spécifiés et mal spécifiés. Nous confirmons notre étude analytique par le biais de simulations approfondies de la précision relative de la prévision des différentes techniques de prévision à plusieurs étapes. A travers ces simulations, nous soutenons l'analyse asymptotique et étudions les conditions qui rendent le PLS meilleur que l'IMS ou le DMS.Au chapitre 3, nous menons une étude empirique de la prévision en plusieurs étapes basée sur des modèles de AR univariés et nous nous concentrons sur les 121 séries chronologiques mensuelles macroéconomiques aux États-Unis.Nous fournissons une analyse empirique visant à déterminer les circonstances qui rendent PLS préférable à IMS ou à DMS. Pour une comparaison plus facile avec la littérature, nous suivons Marcellino et al. (2006) et McCracken & McGillicuddy (2019) à bien des égards. En outre, nous étendons leurs résultats dans certaines directions, telles que l’évaluation de la prévision de trajectoire, les techniques de mesure alternatives et différents sous-échantillons.Nous explorons les avantages en relation avec la persistance de la série mesurée par le degré d'intégration fractionnaire.A travers cette analyse empirique, nous reconfirmons les résultats des études précédentes et découvrons plusieurs faits nouveaux: (i) les avantages relatifs du PLS par rapport au système IMS ont tendance à disparaître à mesure que l'horizon de prévision se développe; (ii) le PLS est généralement meilleur lorsque le modèle utilise des décalages courts; et (iii) les PLS fonctionnent mieux que le système IMS lorsque les données subissent des périodes de forte volatilité.Le dernier chapitre étend le chapitre 3 aux modèles multivariés. Nous comparons une brève étude analytique de la raison d'être du PLS, puis…
Advisors/Committee Members: Chevillon, Guillaume (thesis director).
Subjects/Keywords: Forecasting; Econometrics; Time series; Econometrics; Forecasting; Time series
Record Details
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Record Details
Similar Records
Cite
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Kwon, J. (2019). Three Essays on Multi-step forecasting with Partial Least Squares : Multi-step forecasting with Partial Least Squares. (Doctoral Dissertation). Cergy-Pontoise. Retrieved from http://www.theses.fr/2019CERG1035
Chicago Manual of Style (16th Edition):
Kwon, Joonsuk. “Three Essays on Multi-step forecasting with Partial Least Squares : Multi-step forecasting with Partial Least Squares.” 2019. Doctoral Dissertation, Cergy-Pontoise. Accessed February 27, 2021.
http://www.theses.fr/2019CERG1035.
MLA Handbook (7th Edition):
Kwon, Joonsuk. “Three Essays on Multi-step forecasting with Partial Least Squares : Multi-step forecasting with Partial Least Squares.” 2019. Web. 27 Feb 2021.
Vancouver:
Kwon J. Three Essays on Multi-step forecasting with Partial Least Squares : Multi-step forecasting with Partial Least Squares. [Internet] [Doctoral dissertation]. Cergy-Pontoise; 2019. [cited 2021 Feb 27].
Available from: http://www.theses.fr/2019CERG1035.
Council of Science Editors:
Kwon J. Three Essays on Multi-step forecasting with Partial Least Squares : Multi-step forecasting with Partial Least Squares. [Doctoral Dissertation]. Cergy-Pontoise; 2019. Available from: http://www.theses.fr/2019CERG1035
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Open Access Theses and Dissertations