Browsing by Subject "Markov chain Monte Carlo"
Now showing items 1-10 of 10
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Advances in Bayesian Modeling of Protein Structure Evolution
(2018)This thesis contributes to a statistical modeling framework for protein sequence and structure evolution. An existing Bayesian model for protein structure evolution is extended in two unique ways. Each of these model extensions ... -
Approximate Bayesian Computation for Complex Dynamic Systems
(2013)This thesis focuses on the development of ABC methods for statistical modeling in complex dynamic systems. Motivated by real applications in biology, I propose computational strategies for Bayesian inference in contexts ... -
Bayesian Analysis and Computational Methods for Dynamic Modeling
(2009)Dynamic models, also termed state space models, comprise an extremely rich model class for time series analysis. This dissertation focuses on building state space models for a variety of contexts and computationally efficient ... -
Bayesian Inference in Large-scale Problems
(2016)Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point ... -
Computational Challenges to Bayesian Density Discontinuity Regression
(2022)Many policies subject an underlying continuous variable to an artificial cutoff. Agents may regulate the magnitude of the variable to stay on the preferred side of a known cutoff, which results in the form of a jump discontinuity ... -
Data augmentation for models based on rejection sampling.
(Biometrika, 2016-06)We present a data augmentation scheme to perform Markov chain Monte Carlo inference for models where data generation involves a rejection sampling algorithm. Our idea is a simple scheme to instantiate the rejected proposals ... -
Finite population estimators in stochastic search variable selection
(BIOMETRIKA, 2012-12) -
Joint modeling of multiple repeated measures and survival data using multidimensional latent trait linear mixed model.
(Statistical methods in medical research, 2018-10-11)Impairment caused by Amyotrophic lateral sclerosis (ALS) is multidimensional (e.g. bulbar, fine motor, gross motor) and progressive. Its multidimensional nature precludes a single outcome to measure disease progression. ... -
Monitoring and Improving Markov Chain Monte Carlo Convergence by Partitioning
(2015)Since Bayes' Theorem was first published in 1762, many have argued for the Bayesian paradigm on purely philosophical grounds. For much of this time, however, practical implementation of Bayesian methods was limited to a ... -
Random Orthogonal Matrices with Applications in Statistics
(2019)This dissertation focuses on random orthogonal matrices with applications in statistics. While Bayesian inference for statistical models with orthogonal matrix parameters is a recurring theme, several of the results on random ...
