Browsing Mathematics (Faculty of) by Title
Now showing items 1739-1758 of 3027
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Multiple imputation for the analysis of incomplete compound variables
(Wiley, 2015-06)In many settings interest lies in modelling a compound variable defined as a function of two or more component variables. When one or more of the components are missing, the compound variable is not observed and a strategy ... -
Multiple Object Tracking with Occlusion Handling
(University of Waterloo, 2010-02-17)Object tracking is an important problem with wide ranging applications. The purpose is to detect object contours and track their motion in a video. Issues of concern are to be able to map objects correctly between two ... -
Multiple testing using the posterior probability of half-space: application to gene expression data.
(University of Waterloo, 2005)We consider the problem of testing the equality of two sample means, when the number of tests performed is large. Applying this problem to the context of gene expression data, our goal is to detect a set of genes ... -
Multiplicities of Linear Recurrence Sequences
(University of Waterloo, 2006)In this report we give an overview of some of the major results concerning the multiplicities of linear recurrence sequences. We first investigate binary recurrence sequences where we exhibit a result due to Beukers and ... -
Multiply Robust Empirical Likelihood Inference for Missing Data and Causal Inference Problems
(University of Waterloo, 2019-06-06)Missing data are ubiquitous in many social and medical studies. A naive complete-case (CC) analysis by simply ignoring the missing data commonly leads to invalid inferential results. This thesis aims to develop statistical ... -
Multiscale GARCH Modeling and Inference
(University of Waterloo, 2018-10-11)The motivation behind this thesis is the shortage of formal statistical inference methods in the literature for testing whether a time series model is consistent with a sample at multiple sampling frequencies simultaneously. ... -
Multiscale Methods in Image Modelling and Image Processing
(University of Waterloo, 2005)The field of modelling and processing of 'images' has fairly recently become important, even crucial, to areas of science, medicine, and engineering. The inevitable explosion of imaging modalities and approaches ... -
Multiscale models of kidney function and diseases
(Elsevier, 2019-09)The kidney is a complex system whose function is the result of synergistic operations among a number of biological processes. The spatial and functional scales of those processes span a wide range. To interrogate kidney ... -
Multistate analysis from cross-sectional and auxiliary samples
(Wiley, 2020-02-20)Epidemiological studies routinely involve cross‐sectional sampling of a population comprised of individuals progressing through life history processes. We consider features of a cross‐sectional sample in terms of the ... -
A Multistate Model for Bivariate Interval-Censored Failure Time Data
(Wiley, 2008-12)Interval-censored life-history data arise when the events of interest are only detectable at periodic assessments. When interest lies in the occurrence of two such events, bivariate-interval censored event time data are ... -
Multistate Models for Biomarker Processes
(University of Waterloo, 2014-08-25)Multistate models are widely used for describing life history processes. In studies where individuals are observed continuously, the transition times between states are known exactly. However, when individuals are observed ... -
Multivariate First-Passage Models in Credit Risk
(University of Waterloo, 2008-10-17)This thesis deals with credit risk modeling and related mathematical issues. In particular we study first-passage models for credit risk, where obligors default upon first passage of a ``credit quality" process to ... -
Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models
(University of Waterloo, 2013-01-24)Longitudinal studies, where data on study subjects are collected over time, is increasingly involving multivariate longitudinal responses. Frequently, the heterogeneity observed in a multivariate longitudinal response can ... -
Multivariate Multiscale Analysis of Neural Spike Trains
(University of Waterloo, 2013-12-17)This dissertation introduces new methodologies for the analysis of neural spike trains. Biological properties of the nervous system, and how they are reflected in neural data, can motivate specific analytic tools. Some of ... -
Multivariate Risk Measures for Portfolio Risk Management
(University of Waterloo, 2021-01-29)In portfolio risk management, the main foci are to control the aggregate risk of the entire portfolio and to understand the contribution of each individual risk unit in the portfolio to the aggregate risk. When univariate ... -
Multivariate Time Series Analysis of the Investment Guarantee in Canadian Segregated Fund Products
(University of Waterloo, 2008-05-23)In the context of the guarantee liability valuation, the sophisticated fund-of-funds structure, of some Canadian segregated fund products, often requires us to model multiple market indices simultaneously in order to ... -
Multivariate Triangular Quantile Maps for Novelty Detection
(University of Waterloo, 2024-05-21)Novelty detection, a fundamental task in the field of machine learning, has drawn a lot of recent attention due to its wide-ranging applications and the rise of neural approaches. In this thesis, we present a general ... -
Mutation rates of Escherichia coli with different balanced growth rates: a new fluctuation test protocol and phenotypic lag adjustments
(University of Waterloo, 2020-10-23)Bacteria are the oldest, most abundant life form on the planet, and every other organism’s livelihood is dependent on them. The bacteria Escherichia coli (E. coli) is commonly used in microbiology as a model organism to ... -
Mutual Information Based Methods to Localize Image Registration
(University of Waterloo, 2005)Modern medicine has become reliant on medical imaging. Multiple modalities, e. g. magnetic resonance imaging (MRI), computed tomography (CT), etc. , are used to provide as much information about the patient as ... -
Naive Bayes Data Complexity and Characterization of Optima of the Unsupervised Expected Likelihood
(University of Waterloo, 2017-09-21)The naive Bayes model is a simple model that has been used for many decades, often as a baseline, for both supervised and unsupervised learning. With a latent class variable it is one of the simplest latent variable models, ...