Browsing Duke Scholarly Works by Affiliation of Duke Author(s) "Statistical Science"
Now showing items 2140 of 169

An elementary proof of the existence and uniqueness theorem for the NavierStokes equations
(Communications in Contemporary Mathematics, 19991101) 
An Empirical Comparison of Multiple Imputation Methods for Categorical Data
(The American Statistician, 20170403)© 2017 American Statistical Association. Multiple imputation is a common approach for dealing with missing values in statistical databases. The imputer fills in missing values with draws from predictive models estimated ... 
Analysis of clickevoked otoacoustic emissions by concentration of frequency and time: Preliminary results from normal hearing and Ménière's disease ears
(AIP Conference Proceedings, 20180531)© 2018 Author(s). The presence of clickevoked (CE) otoacoustic emissions (OAEs) has been clinically accepted as an indicator of normal cochlear processing of sounds. For treatment and diagnostic purposes, however, clinicians ... 
Association between DNA Damage Response and Repair Genes and Risk of Invasive Serous Ovarian Cancer
(PLOS ONE, 20100408) 
Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.
(PLoS One, 20100408)BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53mediated damage response and serous ovarian cancer risk using casecontrol data from the North Carolina Ovarian Cancer Study (NCOCS), ... 
Asymptotic coupling and a general form of Harris' theorem with applications to stochastic delay equations
(Probability Theory and Related Fields, 20110301)There are many Markov chains on infinite dimensional spaces whose onestep transition kernels are mutually singular when starting from different initial conditions. We give results which prove unique ergodicity under minimal ... 
Automatic Sterilization TrashCan with Application of UVLED and Photocatalytic Oxidation
(Northern Taiwan Journal, 20090331)The main purpose of this research work is to make the traditional trashcan not distribute odor and not be approached by mosquitoes and bacteria, and to modify other shortcomings. We are going to design a multipurpose trashcan ... 
Bagging and the Bayesian Bootstrap
(Artificial Intelligence and Statistics, 2001)Bagging is a method of obtaining more ro bust predictions when the model class under consideration is unstable with respect to the data, i.e., small changes in the data can cause the predicted values to change significantly. ... 
Bayes and empiricalBayes multiplicity adjustment in the variableselection problem
(Annals of Statistics, 20101001)This paper studies the multiplicitycorrection effect of standard Bayesian variableselection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian ... 
Bayesian crack detection in ultra high resolution multimodal images of paintings
(2013 18th International Conference on Digital Signal Processing, DSP 2013, 20131206)The preservation of our cultural heritage is of paramount importance. Thanks to recent developments in digital acquisition techniques, powerful image analysis algorithms are developed which can be useful noninvasive tools ... 
Bayesian Gaussian Copula Factor Models for Mixed Data.
(J Am Stat Assoc, 20130601)Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent ... 
Bayesian generalized product partition model
(Statistica Sinica, 20100701)Starting with a carefully formulated Dirichlet process (DP) mixture model, we derive a generalized product partition model (GPPM) in which the partition process is predictordependent. The GPPM generalizes DP clustering ... 
Bayesian inference for genomic data integration reduces misclassification rate in predicting proteinprotein interactions.
(PLoS Comput Biol, 201107)Proteinprotein interactions (PPIs) are essential to most fundamental cellular processes. There has been increasing interest in reconstructing PPIs networks. However, several critical difficulties exist in obtaining reliable ... 
Bayesian inference of the number of factors in geneexpression analysis: application to human virus challenge studies
(BMC BIOINFORMATICS, 20101109) 
Bayesian inference of the number of factors in geneexpression analysis: application to human virus challenge studies.
(BMC Bioinformatics, 20101109)BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques ... 
Bayesian latent pattern mixture models for handling attrition in panel studies with refreshment samples
(Annals of Applied Statistics, 20160301)Many panel studies collect refreshment samples—new, randomly sampled respondents who complete the questionnaire at the same time as a subsequent wave of the panel. With appropriate modeling, these samples can be leveraged ... 
Bayesian Learning in Sparse Graphical Factor Models via Variational MeanField Annealing.
(J Mach Learn Res, 20100501)We describe a class of sparse latent factor models, called graphical factor models (GFMs), and relevant sparse learning algorithms for posterior mode estimation. Linear, Gaussian GFMs have sparse, orthogonal factor loadings ... 
Bayesian Model Averaging in the MOpen Framework
(Bayesian Theory and Applications, 2013)This chapter presents a model averaging approach in the Mopen setting using sample reuse methods to approximate the predictive distribution of future observations. It first reviews the standard Mclosed Bayesian Model ... 
Bayesian model averaging: A tutorial  Comment
(STATISTICAL SCIENCE, 199911)