Browsing Statistics and Actuarial Science by Title
Now showing items 311-330 of 363
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Sparse Models in High-Dimensional Dependence Modelling and Index Tracking
(University of Waterloo, 2017-01-17)This thesis is divided into two parts. The first part proposes parsimonious models to the vine copula. The second part is devoted to the index tracking problem. Vine copulas provide a flexible tool to capture asymmetry ... -
State-dependent Modeling of Default Rates
(University of Waterloo, 2021-09-29)Risk-weight function is the most popular formula for banking regulations used to calculate the amount of backup deposit that banks need to hold in order to bear extraordinary losses. The model behind the formula was ... -
Static and Dynamic Modelling of Credit Default Risk: Tails, Moments, and Calibration
(University of Waterloo, 2014-08-26)Credit risk modelling can take many different approaches. Each method has its strengths and weaknesses and studying a variety of them can help find new ways of performing credit risk analysis. We present here three different ... -
Statistical Analysis of EEG Phase Shift Events
(University of Waterloo, 2014-10-02)This thesis develops statistical methods for the identification, and analysis of phase shift events, i.e. sudden changes in the timing relationship between coupled oscillators. Phase shifts events occur in many complex ... -
Statistical Analysis with Non-probability Survey Samples
(University of Waterloo, 2020-09-25)The goal of this thesis is to develop inferential procedures with non-probability survey samples. In recent years, the use of non-probability survey samples has become one of the most important topics in the area. Contrast ... -
Statistical Inference and Pricing for Regime Switching Models in Finance and Insurance
(University of Waterloo, 2016-09-02)This thesis studies the estimation, goodness-of-fit testing, pricing and sampling problems for regime switching models, which are popularly used in financial markets. Specifically, we consider such models whose distributions ... -
Statistical Inference on Stochastic Graphs
(University of Waterloo, 2011-07-08)This thesis considers modelling and applications of random graph processes. A brief review on contemporary random graph models and a general Birth-Death model with relevant maximum likelihood inference procedure are ... -
Statistical Issues in Modeling Chronic Disease in Cohort Studies
(Springer, 2014)Observational cohort studies of individuals with chronic disease provide information on rates of disease progression, the effect of fixed and time-varying risk factors, and the extent of heterogeneity in the course of ... -
Statistical Learning and Stochastic Process for Robust Predictive Control of Vehicle Suspension Systems
(University of Waterloo, 2017-09-12)Predictive controllers play an important role in today's industry because of their capability of verifying optimum control signals for nonlinear systems in a real-time fashion. Due to their mathematical properties, such ... -
Statistical Learning Approaches to Some Classification Problems
(University of Waterloo, 2017-08-01)Classification is essential in statistical learning. This thesis deals with three topics in classification: multi-label classification, nonparametric multi-class classification and a special type of text categorization ... -
Statistical Learning in Drug Discovery via Clustering and Mixtures
(University of Waterloo, 2007-09-20)In drug discovery, thousands of compounds are assayed to detect activity against a biological target. The goal of drug discovery is to identify compounds that are active against the target (e.g. inhibit a virus). Statistical ... -
Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation
(University of Waterloo, 2020-07-17)This thesis discusses statistical problems in event history data analysis including survival analysis and multistate models. Research questions in this thesis are motivated by the Nun Study, which contains longevity data ... -
Statistical Methods for High Throughput Screening Drug Discovery Data
(University of Waterloo, 2005)High Throughput Screening (HTS) is used in drug discovery to screen large numbers of compounds against a biological target. Data on activity against the target are collected for a representative sample of compounds ... -
Statistical Methods for Incomplete Covariates and Two-Phase Designs
(University of Waterloo, 2013-01-24)Incomplete data is a pervasive problem in health research, and as a result statistical methods enabling inference based on partial information play a critical role. This thesis explores estimation of regression coefficients ... -
Statistical methods for incomplete data: Some results on model misspecification
(Sage Publishing, 2017-02-01)Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour ... -
Statistical Methods for Large-scale Multiple Testing Problems
(University of Waterloo, 2019-04-26)A large-scale multiple testing problem simultaneously tests thousands or even millions of null hypotheses, and it is widely used in different fields, for example genetics and astronomy. An error rate serves as a measure ... -
Statistical Methods for Life History Analysis Involving Latent Processes
(University of Waterloo, 2014-05-22)Incomplete data often arise in the study of life history processes. Examples include missing responses, missing covariates, and unobservable latent processes in addition to right censoring. This thesis is on the development ... -
Statistical Methods for Multi-State Analysis of Incomplete Longitudinal Data
(University of Waterloo, 2008-09-25)Analyses of longitudinal categorical data are typically based on semiparametric models in which covariate effects are expressed on marginal probabilities and estimation is carried out based on generalized estimating ... -
Statistical Methods in the Search for a Dominant Cause of Variation
(University of Waterloo, 2023-12-15)Excessive variation in critical-to-quality characteristics, referred to as process outputs in this thesis, is a common issue in manufacturing industries. Most variation reduction frameworks initially investigate the process ... -
Statistical Methods on Survival Data with Measurement Error
(University of Waterloo, 2014-08-25)In survival data analysis, covariates are often subject to measurement error. A naive analysis with measurement error ignored commonly leads to biased estimation of parameters of survival models. Measurement error also ...