Now showing items 169-188 of 359

    • L1-Penalized Ordinal Regression and Bayesian Variable Selection for Linear Models with Multiple Responses 

      Chang, Ya-Ting (University of Waterloo, 2015-05-20)
      Polychotomous ordinal response data are often analyzed by first introduce a latent continuous variable which can be modeled as an ordinary regression problem with the presence of covariates by using Markov chain Monte Carlo ...
    • Large Data-to-Text Generation 

      Sarangian, Varnan (University of Waterloo, 2023-05-16)
      This thesis presents a domain-driven approach to sports game summarization, a specific instance of large data-to-text generation (DTG). We first address the data fidelity issue in the Rotowire dataset by supplementing ...
    • A Latent Health Factor Model for Estimating Estuarine Ecosystem Health 

      Wu, Margaret (University of Waterloo, 2009-05-20)
      Assessment of the “health” of an ecosystem is often of great interest to those interested in monitoring and conservation of ecosystems. Traditionally, scientists have quantified the health of an ecosystem using multimetric ...
    • Learning From Almost No Data 

      Sucholutsky, Ilia (University of Waterloo, 2021-06-15)
      The tremendous recent growth in the fields of artificial intelligence and machine learning has largely been tied to the availability of big data and massive amounts of compute. The increasingly popular approach of training ...
    • Leveraged Plans for Measurement System Assessment 

      Browne, Ryan (University of Waterloo, 2009-08-20)
      In manufacturing, measurement systems are used to control processes and inspect parts with the goal of producing high quality product for the customer. Modern Quality Systems require the periodic assessment of key measurement ...
    • Life History Analysis with Response-Dependent Observation 

      Zhong, Yujie (University of Waterloo, 2015-05-14)
      This thesis deals with statistical issues in the analysis of dependent failure time data under complex observation schemes. These observation schemes may yield right-censored, interval-censored and current status data and ...
    • Linearization Methods in Time Series Analysis 

      Chen, Bei (University of Waterloo, 2011-09-30)
      In this dissertation, we propose a set of computationally efficient methods based on approximating/representing nonlinear processes by linear ones, so-called linearization. Firstly, a linearization method is introduced for ...
    • Local Mixture Model in Hilbert Space 

      Zhiyue, Huang (University of Waterloo, 2010-01-26)
      In this thesis, we study local mixture models with a Hilbert space structure. First, we consider the fibre bundle structure of local mixture models in a Hilbert space. Next, the spectral decomposition is introduced in order ...
    • Lognormal Mixture Model for Option Pricing with Applications to Exotic Options 

      Fang, Mingyu (University of Waterloo, 2012-08-23)
      The Black-Scholes option pricing model has several well recognized deficiencies, one of which is its assumption of a constant and time-homogeneous stock return volatility term. The implied volatility smile has been studied ...
    • Longevity Risk Management: Models and Hedging Strategies 

      Zhou, Kenneth Qian (University of Waterloo, 2019-04-17)
      Longevity risk management is becoming increasingly important in the pension and life insurance industries. The unexpected mortality improvements observed in recent decades are posing serious concerns to the financial ...
    • Longitudinal Data Analysis with Composite Likelihood Methods 

      Li, Haocheng (University of Waterloo, 2012-08-10)
      Longitudinal data arise commonly in many fields including public health studies and survey sampling. Valid inference methods for longitudinal data are of great importance in scientific researches. In longitudinal studies, ...
    • Marginal Causal Sub-Group Analysis with Incomplete Covariate Data 

      Cuerden, Meaghan (University of Waterloo, 2019-01-11)
      Incomplete data arises frequently in health research studies designed to investigate the causal relationship between a treatment or exposure, and a response of interest. Statistical methods for conditional causal effect ...
    • Marginal Methods for Multivariate Time to Event Data 

      Wu, Longyang (University of Waterloo, 2012-04-30)
      This thesis considers a variety of statistical issues related to the design and analysis of clinical trials involving multiple lifetime events. The use of composite endpoints, multivariate survival methods with dependent ...
    • Markovian Approaches to Joint-life Mortality with Applications in Risk Management 

      Ji, Min (University of Waterloo, 2011-08-16)
      The combined survival status of the insured lives is a critical problem when pricing and reserving insurance products with more than one life. Our preliminary experience examination of bivariate annuity data from a large ...
    • Martingale Property and Pricing for Time-homogeneous Diffusion Models in Finance 

      Cui, Zhenyu (University of Waterloo, 2013-08-09)
      The thesis studies the martingale properties, probabilistic methods and efficient unbiased Monte Carlo simulation methods for various time-homogeneous diffusion models commonly used in mathematical finance. Some of the ...
    • A mathematical foundation for the use of cliques in the exploration of data with navigation graphs 

      Shuldiner, Pavel (University of Waterloo, 2023-01-19)
      Navigation graphs were introduced by Hurley and Oldford (2011) as a graph-theoretic framework for exploring data sets, particularly those with many variables. They allow the user to visualize one small subset of the variables ...
    • Matrix analytic methods for computations in risk theory 

      Kim, Sung Soo (University of Waterloo, 2019-01-15)
      The introduction of matrix analytic methods in risk theory has marked a significant progress in computations in risk theory. Matrix analytic methods have proven to be powerful computational tools for numerically analyzing ...
    • Matrix-Variate Regression with Measurement Error 

      Fang, Junhan (University of Waterloo, 2020-09-28)
      Matrix-variate regression models are useful for featuring data with a matrix structure, such as brain imaging data. However, those methods do not apply to data with measurement error or misclassification. While mismeasurement ...
    • Maximum likelihood estimation of first-passage structural credit risk models correcting for the survivorship bias 

      Amaya, Diego; Boudreault, Mathieu; McLeish, Don L. (Elsevier, 2019-03)
      The survivorship bias in credit risk modeling is the bias that results in parameter estimates when the survival of a company is ignored. We study the statistical properties of the maximum likelihood estimator (MLE) accounting ...
    • Measurement Error and Misclassification in Interval-Censored Life History Data 

      White, Bethany Joy Giddings (University of Waterloo, 2007-05-04)
      In practice, data are frequently incomplete in one way or another. It can be a significant challenge to make valid inferences about the parameters of interest in this situation. In this thesis, three problems involving ...

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