• Scalability aspects of data cleaning 

  Saxena, Hemant (University of Waterloo, 2021-01-27)

  Data cleaning has become one of the important pre-processing steps for many data science, data analytics, and machine learning applications. According to a survey by Gartner, more than 25% of the critical data in the world's ...

• Investigations into quantum light-matter interactions, their approximations and applications 

  Funai, Nicholas (University of Waterloo, 2021-01-26)

  Devoting some thought to the interactions between light and matter quickly conjure a myriad of different possibilities; different models for light and matter, different possible interaction Hamiltonians, different simplifying ...

• Generalizations of All-or-Nothing Transforms and their Application in Secure Distributed Storage 

  Navid, Nasr Esfahani (University of Waterloo, 2021-01-26)

  An all-or-nothing transform is an invertible function that maps s inputs to s outputs such that, in the calculation of the inverse, the absence of only one output makes it impossible for an adversary to obtain any information ...

• Scaling Machine Learning Data Repair Systems for Sparse Datasets 

  Attia, Omar (University of Waterloo, 2021-01-21)

  Machine learning data repair systems (e.g. HoloClean) have achieved state-of-the-art performance for the data repair problem on many datasets. However, these systems face significant challenges with sparse datasets. In ...

• Variational Stokes with Polynomial Reduced Fluid Model 

  Panuelos, Jonathan (University of Waterloo, 2021-01-21)

  Standard fluid simulators often apply operator splitting to independently solve for pressure and viscous stresses. This decoupling, however, induces incorrect free surface boundary conditions. Such methods are unable to ...

• Applications of Projection Pursuit in Functional Data Analysis: Goodness-of- fit, Forecasting, and Change-point Detection 

  Xie, Yijun (University of Waterloo, 2021-01-20)

  Dimension reduction methods for functional data have been avidly studied in recent years. However, existing methods are primarily based on summarizing the data by their projections into principal component subspaces, namely ...

• Correlated Data Analysis with Copula Models or Bayesian Nonparametric Methods 

  Zhuang, Haoxin (University of Waterloo, 2021-01-20)

  Different types of correlated data arise commonly in many studies and present considerable challenges in modeling and characterizing complex dependence structures. This thesis considers statistical issues in analyzing such ...

• Regression with incomplete multivariate surrogate responses for a latent covariate 

  Shen, Hua; Cook, Richard J. (Taylor & Francis, 2020-07-29)

  We consider the setting in which a categorical exposure variable of interest can only be measured subject to misclassification via surrogate variables. These surrogate variables may represent the classification of an ...

• Composite likelihood for aggregate data from clustered multistate processes under intermittent observation 

  Jiang, Shu; Cook, Richard J. (Taylor & Francis, 2019-03-11)

  Markov processes offer a useful basis for modeling the progression of organisms through successive stages of their life cycle. When organisms are examined intermittently in developmental studies, likelihoods can be constructed ...

• Failure time studies with intermittent observation and losses to follow-up 

  Cook, Richard J.; Lawless, Jerald F. (Wiley, 2020-12-01)

  In health research interest often lies in modeling a failure time process but in many cohort studies failure status is only determined at scheduled assessment times. While the assessment times may be fixed upon study entry, ...

• On the Automatic Coding of Text Answers to Open-ended Questions in Surveys 

  He, Zhoushanyue (University of Waterloo, 2021-01-13)

  Open-ended questions allow participants to answer survey questions without any constraint. Responses to open-ended questions, however, are more difficult to analyze quantitatively than close-ended questions. In this thesis, ...

• Budget-Constrained Optimal Insurance with an Upper Limit on the Insurer's Exposure 

  Coke, Oma (University of Waterloo, 2021-01-13)

  This thesis studies the problem of budget-constrained optimal insurance indemnification when the insurer imposes an upper limit on disbursement. In balancing the trade-off between the cost of paying the insurance premium ...

• A mixture model for bivariate interval-censored failure times with dependent susceptibility 

  Jiang, Shu; Cook, Richard J. (Springer, 2020-03-07)

  Interval-censored failure times arise when the status with respect to an event of interest is only determined at intermittent examination times. In settings where there exists a sub-population of individuals who are not ...

• Mitigating bias from intermittent measurement of time-dependent covariates in failure time analysis 

  Jiang, Shu; Cook, Richard J.; Zeng, Leilei (Wiley, 2020-06-15)

  Cox regression models are routinely fitted to examine the association between time-dependent markers and a failure time when analyzing data from clinical registries. Typically, the marker values are measured periodically ...

• Score tests based on a finite mixture model of Markov processes under intermittent observation 

  Jiang, Shu; Cook, Richard J. (Wiley, 2019-07-20)

  A mixture model is described, which accommodates different Markov processes governing disease progression in a finite set of latent classes. We give special attention to the setting in which individuals are examined ...

• On estimands arising from misspecified semiparametric rate-based analysis of recurrent episodic conditions 

  Lee, Jooyoung; Cook, Richard J. (Wiley, 2019-11-10)

  Marginal rate-based analyses are widely used for the analysis of recurrent events in clinical trials. In many areas of application, the events are not instantaneous but rather signal the onset of a symptomatic episode ...

• Dependence modeling for multi-type recurrent events via copulas 

  Lee, Jooyoung; Cook, Richard J. (Wiley, 2019-09-20)

  When several types of recurrent events may arise, interest often lies in marginal modeling and studying the nature of the dependence structure. In this paper, we propose a multivariate mixed-Poisson model with the dependence ...

• Cohort study design for illness-death processes with disease status under intermittent observation 

  Moon, Nathalie C.; Zeng, Leilei; Cook, Richard J. (Taylor & Francis, 2019-12-12)

  Cohort studies are routinely conducted to learn about the incidence or progression rates of chronic diseases. The illness-death model offers a natural framework for joint consideration of non-fatal events in the semi-competing ...

• Tracing studies in cohorts with attrition: Selection models for efficient sampling 

  Moon, Nathalie C.; Zeng, Leilei; Cook, Richard J. (Wiley, 2018-07-10)

  Cohort studies of chronic diseases involve recruitment and longitudinal followup of affected individuals with a view to studying the effect of risk factors on disease progression and death. When the time to withdrawal from ...

• Some Stochastic Optimization Problems in Reinsurance and Insurance 

  Cao, Jingyi (University of Waterloo, 2021-01-12)

  Insurance, which hedges against the risk of a contingent loss, is an indispensable risk management tool for both institutions and individuals. Reinsurance, namely, a form of insurance accessible to insurers, helps limit ...

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