Browsing Faculty of Arts and Sciences by FAS Department "Statistics"
Now showing items 1-20 of 239
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A Grand Journey of Statistical Hierarchical Modelling
(2017-05-03)This thesis presents three research reports composed by the candidate and his collaborators on different perspectives and applications of statistical hierarchical modelling, which seeks to connect the observed quantities ... -
Active vs. Passive Decisions and Crowd-Out in Retirement Savings Accounts: Evidence from Denmark
(Oxford University Press (OUP), 2014)Using 41 million observations on savings for the population of Denmark, we show that the effects of retirement savings policies on wealth accumulation depend on whether they change savings rates by active or passive choice. ... -
An Adaptive Exchange Algorithm for Sampling From Distributions With Intractable Normalizing Constants
(Informa UK Limited, 2016)Sampling from the posterior distribution for a model whose normalizing constant is intractable is a long-standing problem in statistical research. We propose a new algorithm, adaptive auxiliary variable exchange algorithm, ... -
Advances in Empirical Bayes Modeling and Bayesian Computation
(2013-08-14)Chapter 1 of this thesis focuses on accelerating perfect sampling algorithms for a Bayesian hierarchical model. A discrete data augmentation scheme together with two different parameterizations yields two Gibbs samplers ... -
Advances in Statistical Network Modeling and Nonlinear Time Series Modeling
(2018-05-11)The thesis is composed of two independent topics: statistical network modeling and nonlinear time series modeling. With the increasing demand of network data analysis, we present two statistical network models and inferences, ... -
Advances in the Normal-Normal Hierarchical Model
(2014-06-06)This thesis consists of results relating to the theoretical and computational advances in modeling the Normal-Normal hierarchical model. -
Aggregation Among Binary, Count, and Duration Models: Estimating the Same Quantities from Different Levels of Data
(Oxford University Press, 2001)Binary, count, and duration data all code discrete events occurring at points in time. Although a single data generation process can produce all of these three data types, the statistical literature is not very helpful in ... -
Analysis, Modeling, and Optimal Experimental Design under Uncertainty: From Carbon Nano-Structures to 3D Printing
(2016-04-27)In this thesis, we develop approaches for carrying out inference and model-based experimental design, under both internal and external sources of uncertainty. Specifically, in Chapter 1, we develop a stochastic growth model ... -
Analyzing Second Stage Ecological Regressions: Comment on Herron and Shotts
(Oxford University Press, 2003) -
Aneuploidy Prediction and Tumor Classification with Heterogeneous Hidden Conditional Random Fields
(Oxford University Press, 2008)Motivation: The heterogeneity of cancer cannot always be recognized by tumor morphology, but may be reflected by the underlying genetic aberrations. Array-CGH methods provide highthroughput data on genetic copy numbers, ... -
AP statistics: Passion, paradox, and pressure (Part II).
(American Statistical Association, 2010) -
Association pattern discovery via theme dictionary models
(Wiley-Blackwell, 2013)Discovering patterns from a set of text or, more generally, categorical data is an important problem in many disciplines such as biomedical research, linguistics, artificial intelligence and sociology. We consider here the ... -
Assumptions behind Intercoder Reliability Indices
(Routledge, 2012)Inter-coder reliability is the most often used quantitative indicator of measurement quality in content studies. Researchers in psychology, sociology, education, medicine, marketing and other disciplines also use reliability ... -
Asymptotic and finite-sample properties of estimators based on stochastic gradients
(Institute of Mathematical Statistics, 2017)Stochastic gradient descent procedures have gained popularity for parameter estimation from large data sets. However, their statis- tical properties are not well understood, in theory. And in practice, avoiding numerical ... -
Asymptotic Theory of Rerandomization in Treatment-Control Experiments
Although complete randomization ensures covariate balance on average, the chance for ob- serving significant differences between treatment and control covariate distributions increases with many covariates. Rerandomization ... -
Bayesian Biclustering of Gene Expression Data
(BioMed Central, 2008)Background: Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset ... -
Bayesian Biclustering on Discrete Data: Variable Selection Methods
(2013-10-18)Biclustering is a technique for clustering rows and columns of a data matrix simultaneously. Over the past few years, we have seen its applications in biology-related fields, as well as in many data mining projects. As ... -
Bayesian Functional Data Clustering for Temporal Microarray Data
(Hindawi Publishing Corporation, 2008)We propose a Bayesian procedure to cluster temporal gene expression microarray profiles, based on a mixed-effect smoothing-spline model, and design a Gibbs sampler to sample from the desired posterior distribution. Our ... -
Bayesian Inference for Assessing Effects of Email Marketing Campaigns
(Informa UK Limited, 2016)Email marketing has been an increasingly important tool for today’s businesses. In this paper, we propose a counting-process-based Bayesian method for quantifying the effectiveness of email marketing campaigns in conjunction ... -
Bayesian Inference of Spatial Organizations of Chromosomes
(Public Library of Science, 2013)Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. Recently, chromosome conformation capture (3C) based technologies, such as ...