Browsing Faculty of Arts and Sciences by Keyword "Bayesian inference"
Now showing items 1-14 of 14
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Accelerating Markov chain Monte Carlo via parallel predictive prefetching
(2014-10-21)We present a general framework for accelerating a large class of widely used Markov chain Monte Carlo (MCMC) algorithms. This dissertation demonstrates that MCMC inference can be accelerated in a model of parallel computation ... -
An Analytical and Statistical Toolbox for Per- and Polyfluoroalkyl Substances Biogeochemistry and Source Attribution
(2022-06-06)Per- and polyfluoroalkyl substances (PFAS) are a class of thousands of anthropogenic chemicals that contain one fully fluorinated methyl (-CF3) or methylene (-CF2-) carbon. Their unique chemistry includes thermal stability, ... -
Bayesian Inference Approaches for Particle Trajectory Analysis in Cell Biology
(2013-08-28)Despite the importance of single particle motion in biological systems, systematic inference approaches to analyze particle trajectories and evaluate competing motion models are lacking. An automated approach for robust ... -
Bayesian inference in a class of partially identified models
(The Econometric Society, 2016)This paper develops a Bayesian approach to inference in a class of partially identified econometric models. Models in this class are characterized by a known mapping between a point identified reduced-form parameter µ, and ... -
Contributions to Scalable Bayesian Computation
(2022-05-10)This manuscript presents four projects related to Bayesian computation in large-scale settings. Each chapter is self-contained, and their respective abstracts are given below. Chapter 1: Markov chain Monte Carlo (MCMC) ... -
Inference and Missing Data
(Oxford University Press, 1976)When making sampling distribution inferences about the parameter of the data, {theta}, it is appropriate to ignore the process that causes missing data if the missing data are ‘missing at random’ and the observed data are ... -
Inference from Iterative Simulation Using Multiple Sequences
(Institute of Mathematical Statistics, 1992)The Gibbs sampler, the algorithm of Metropolis and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, however, iterative simulation can give misleading ... -
Not Asked and Not Answered: Multiple Imputation for Multiple Surveys
(American Statistical Association, 1999)We present a method of analyzing a series of independent cross-sectional surveys in which some questions are not answered in some surveys and some respondents do not answer some of the questions posed. The method is also ... -
A phylogenetic revision of the Glaucopsyche section (Lepidoptera: Lycaenidae), with special focus on the Phengaris–Maculinea clade
(Elsevier BV, 2011)Despite much research on the socially parasitic large blue butterflies (genus Maculinea) in the past 40 years, their relationship to their closest relatives, Phengaris, is controversial and the relationships among the ... -
Ranking Relations Using Analogies in Biological and Information Networks
(Institute of Mathematical Statistics, 2010)Analogical reasoning depends fundamentally on the ability to learn and generalize about relations between objects. We develop an approach to rela- tional learning which, given a set of pairs of objects S = {A[super](1) : ... -
Reasoning about ‘irrational’ actions: When intentional movements cannot be explained, the movements themselves are seen as the goal
(Elsevier BV, 2013)Infants and adults are thought to infer the goals of observed actions by calculating the actions’ efficiency as a means to particular external effects, like teaching an object or location. However, many intentional actions ... -
Statistical Learning of Some Complex Systems: From Dynamic Systems to Market Microstructure
(2013-09-27)A complex system is one with many parts, whose behaviors are strongly dependent on each other. There are two interesting questions about complex systems. One is to understand how to recover the true structure of a complex ... -
Stochastic Modeling and Bayesian Inference with Applications in Biophysics
(2013-02-21)This thesis explores stochastic modeling and Bayesian inference strategies in the context of the following three problems: 1) Modeling the complex interactions between and within molecules; 2) Extracting information from ... -
The cognitive contours of punishment
(2023-05-05)People have many ways of influencing others, and one powerful method is through punishment. Punishment can be used to correct the misaligned values of those who commit moral infractions and to instill new values in those ...