Statistics and Actuarial Science
This is the collection for the University of Waterloo's Department of Statistics and Actuarial Science .
Research outputs are organized by type (eg. Master Thesis, Article, Conference Paper).
Waterloo faculty, students, and staff can contact us or visit the UWSpace guide to learn more about depositing their research.
Recent deposits
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Individual insurance choice: A stochastic control approach
(University of Waterloo, 2023-02-28)This thesis applies the stochastic control approach to study the optimal insurance strategy for three problems. The first problem studies the optimal non-life insurance for an individual exhibiting internal habit formation ... -
Causal Inference and Matrix Completion with Correlated Incomplete Data
(University of Waterloo, 2023-01-19)Missing data problems are frequently encountered in biomedical research, social sciences, and environmental studies. When data are missing completely at random, a complete-case analysis may be the easiest approach. However, ... -
A mathematical foundation for the use of cliques in the exploration of data with navigation graphs
(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 ... -
Mortality Prediction using Statistical Learning Approaches
(University of Waterloo, 2022-11-21)Longevity risk, as one of the major risks faced by insurers, has triggered a heated stream of research in mortality modeling among actuaries for effective design/pricing/risk management of insurance products. The idea of ... -
exKidneyBERT: A Language Model for Kidney Transplant Pathology Reports and the Crucial Role of Extended Vocabularies
(University of Waterloo, 2022-09-30)Background: Pathology reports contain key information about the patient’s diagno- sis as well as important gross and microscopic findings. These information-rich clinical reports offer an invaluable resource for clinical ... -
Excursion Sets and Critical Points of Gaussian Random Fields
(University of Waterloo, 2022-09-02)Modeling the critical points of a Gaussian random field is an important challenge in stochastic geometry. In this thesis, we focus on stationary Gaussian random fields and study the locations and types of the critical ... -
End-to-End Whole Slide Image Classification and Search using Set Representations
(University of Waterloo, 2022-08-31)Due to the sheer size of gigapixel whole slide images (WSIs), it is difficult to apply deep learning and computer vision algorithms for digital pathology. Traditional approaches rely on extracting meaningful patches from ... -
Robust Risk Aggregation Techniques and Applications
(University of Waterloo, 2022-08-23)Risk aggregation, which concerns the statistical behaviors of an aggregation position S(X) associated with a random vector X = (X1, . . . , Xn), is an important research topic in risk management, economics, and statistics. ... -
Generalizations to Corrections of Measurement Error Effects for Dynamic Treatment Regimes
(University of Waterloo, 2022-08-19)Measurement error is a pervasive issue in questions of estimation and inference. Generally, any data which are measured with error will render the results of an analysis which ignores this error unreliable. This is a ... -
Dynamic Treatment Regimes with Interference
(University of Waterloo, 2022-08-18)Precision medicine describes healthcare in which patient-level data are used to inform treatment decisions. Within this framework, dynamic treatment regimes (DTRs) are sequences of decision rules that take individual patient ... -
Constructions and applications of quasi-random point sets with negative dependence
(University of Waterloo, 2022-08-17)Randomized Quasi-Monte Carlo (RQMC) methods are used as an alternative to the Monte Carlo (MC) method when performing numeric integration by replacing the random point set of MC with a randomized low-discrepancy sequence ... -
Assessing the accuracy of predictive models with interval-censored data
(Oxford University Press, 2022-01)We develop methods for assessing the predictive accuracy of a given event time model when the validation sample is comprised of case K interval-censored data. An imputation-based, an inverse probability weighted (IPW), and ... -
The illness-death model for family studies
(Oxford University Press, 2021-07)Family studies involve the selection of affected individuals from a disease registry who provide right-truncated ages of disease onset. Coarsened disease histories are then obtained from consenting family members, either ... -
Selection models for efficient two-phase design of family studies
(John Wiley & Sons, Ltd., 2021-01-30)Family studies routinely employ biased sampling schemes in which individuals are randomly chosen from a disease registry and genetic and phenotypic data are obtained from their consenting relatives. We view this as a ... -
Semiparametric recurrent event vs time-to-first-event analyses in randomized trials: Estimands and model misspecification
(John Wiley & Sons Ltd., 2021-04-20)Insights regarding the merits of recurrent event and time-to-first-event analyses are needed to provide guidance on strategies for analyzing intervention effects in randomized trials involving recurrent event responses. ... -
Independence conditions and the analysis of life history studies with intermittent observation
(Oxford University Press, 2021-07)Multistate models provide a powerful framework for the analysis of life history processes when the goal is to characterize transition intensities, transition probabilities, state occupancy probabilities, and covariate ... -
Methods for Merging, Parsimony and Interpretability of Finite Mixture Models
(University of Waterloo, 2022-08-04)To combat the increasing data dimensionality, parsimonious modelling for finite mixture models has risen to be an active research area. These modelling frameworks offer various constraints that can reduce the number of ... -
Data Depth Inference for Difficult Data
(University of Waterloo, 2022-07-18)We explore various ways in which a robust, nonparametric statistical tool, the data depth function can be used to conduct inference on data which could be described as difficult. This can include data which are difficult ... -
Single-Particle Dynamics in Nanoscopic Systems: Statistical Modeling and Inference
(University of Waterloo, 2022-05-24)Our work aims to solve some of the most significant and fundamental theoretical problems involved in the current statistical modeling of stochastic processes in single-molecule experiments, for which a well recognized yet ... -
On First Passage Time Related Problems for Some Insurance Risk Processes
(University of Waterloo, 2022-05-13)For many decades, the study of ruin theory has long been one of the central topics of interest in insurance risk management. Research in this area has largely focused on analyzing the insurer’s solvency risk, which is ...
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