Statistics and Actuarial Science: Recent submissions
Now showing items 21-40 of 361
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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 ... -
Randomized quasi-Monte Carlo methods with applications to quantitative risk management
(University of Waterloo, 2022-05-03)We use randomized quasi-Monte Carlo (RQMC) techniques to construct computational tools for working with normal mixture models, which include automatic integration routines for density and distribution function evaluation, ... -
Design and Analysis of Life History Studies Involving Incomplete Data
(University of Waterloo, 2022-04-26)Incomplete life history data can arise in study designs, coarsened observations, missing covariates, and unobserved latent processes. This thesis consists of three different projects developing statistical models and ... -
Computational Methods for Compositional Epistasis Detection
(University of Waterloo, 2022-04-19)In genetics, the term “epistasis” refers to the phenomenon that the effect of one gene or single-nucleotide polymorphism (SNP) is dependent on the presence of others. Various possibilities of epistasis exist, and the ... -
Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit
(Wiley, 2020-02)In the quest to model various phenomena, the foundational importance of parameter identifiability to sound statistical modeling may be less well appreciated than goodness of fit. Identifiability concerns the quality of ...