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Theses/Dissertations from 2020

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Bayesian hierarchical modeling for the forensic evaluation of handwritten documents, Amy Crawford

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Score-based likelihood ratios and sparse Gaussian processes, Nathaniel Morrissey Garton

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Interaction forward selection in ultra-high-dimensional functional linear models, Rodrigo Plazola Ortiz

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Nowcasting GDP using dynamic factor model: A Bayesian approach, Yixiao Zhang

Theses/Dissertations from 2019

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In-silico guided identification of ciliogenesis candidate genes in a non-conventional animal model, Natalia I. Acevedo Luna

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Topics in portfolio allocation, Oscar Manuel Aguilar

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Extending K-means, Nicholas S. Berry

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Some Bayes methods for biclustering and vector data with binary coordinates, Abhishek Chakraborty

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Improving reliability in the wind energy industry via field failure predictions based on life, maintenance, and dynamic data from supervisory control and data acquisition systems, Michael Stanley Czahor

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Statistical methods for ChIP-seq and microbiome studies using next-generation DNA sequencing data, Emily Goren

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Statistical causal inference methods and spatio-temporal modeling for animal and human health data, Ju Ji

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Topics on small area estimation, multilevel models, and semiparametric imputation, Danhyang Lee

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Incorporating multi-scale structures and physiological processes into the modeling of animal movement., Vianey Caroline Leos Barajas

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Assessing and accounting for correlation in RNA-seq data analysis, Meiling Liu

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Spatially varying coefficient models: Theory and methods, Jingru Mu

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Topics in recurrent event prediction with generalized non-homogeneous Poisson process (NHPP) and electronic circuit troubleshooting with Bayesian inference, Qianqian Shan

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Bayesian hierarchical modeling for disease outbreaks, Nehemias Ulloa

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Studies on semiparametric spatial regression models, Jue Wang

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Topics in functional data analysis and machine learning predictive inference, Haozhe Zhang

Theses/Dissertations from 2018

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Statistical methods for gene expression studies using next-generation sequencing experiments, Ran Bi

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Self-exciting spatio-temporal statistical models for count data with applications to modeling the spread of violence, Nicholas John Clark

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State space models for partially observed biological and agricultural data, Gabriel Demuth

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Developments in MCMC diagnostics and sparse Bayesian learning models, Anand Ulhas Dixit

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Choosing cutoff values for correlated continuous diagnostic data to estimate sensitivity and specificity, Yingzhou Du

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Leveraging genetic time series data to improve detection of natural selection, Luvenia Nicole Hellams

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Modeling crop phenology using remotely sensed data, Colin Lewis-Beck

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Non/Semi-parametric learning from data with complex features, Xinyi Li

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Topics in matrix completion and genomic prediction, Xiaojun Mao

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Multiple hypothesis testing and RNA-seq differential expression analysis accounting for dependence and relevant covariates, Yet Nguyen

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Survey data integration using mass imputation, Seho Park

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Learning algorithms for forensic science applications, Soyoung Park

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Penalized b-splines and their application with an in depth look at the bivariate tensor product penalized b-spline, Michael Price

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Some Bayesian methods for univariate density estimation, Kathleen Rey

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Visualization methods for genealogical and RNA-sequencing studies: Pertinence, software, and applications, Lindsay Rutter

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Random forest robustness, variable importance, and tree aggregation, Andrew Sage

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Approximate Bayesian approaches and semiparametric methods for handling missing data, Hejian Sang

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Selection and assessment of bivariate Markov random field models, Yeon-Jung Seo

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Topics in generalized linear mixed models and spatial subgroup analysis, Xin Wang

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Topics in bootstrap methods for survey sampling and spatially balanced design, Zhonglei Wang

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Statistical methods for microbiome data and antimicrobial resistance analysis, Chaohui Yuan

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Topics in sparse functional data analysis, Weicheng Zhu

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Stratification for area frame surveys with multiple estimation goals, Stephanie Ann Zimmer

Theses/Dissertations from 2017

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Some contributions to k-means clustering problems, Israel A. Almodovar-Rivera

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Bayesian analysis of high-dimensional count data, Ignacio Alvarez-Castro

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Local Polynomial Kernel Smoothing with Correlated Errors, Fan Cao

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Nonlinear models with measurement error: Application to vitamin D, Brenna Curley

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Bagged projection methods for supervised classification in big data, Natalia Da Silva Cousillas

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Accounting for structure in education assessment data using hierarchical models, Jillian Dawn Downey

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Forensic tool mark comparisons: Tests for the null hypothesis of different sources, Jeremy R. Hadler

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Statistical methods for bullet matching, Eric Riemer Hare

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Methods for analysis and uncertainty quantification for processes recorded through sequences of images, Margaret Johnson

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On advancing MCMC-based methods for Markovian data structures with applications to deep learning, simulation, and resampling, Andrea Kaplan

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Bayesian inference of virus evolutionary models from next-generation sequencing data, Emily Anne King

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Statistical methods for estimation, testing, and clustering with gene expression data, Andrew Lithio

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Extending removal and distance-removal models for abundance estimation by modeling detections in continuous time, Adam Martin-Schwarze

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Applications of Bayesian hierarchical models in gene expression and product reliability, Eric Thomas Mittman

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Mixture model and subgroup analysis in nationwide kidney transplant center evaluation, Lanfeng Pan

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Topics in statistical inference for massive data and high-dimensional data, Liuhua Peng

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Measurement error modeling of physical activity data, Daniel Ries

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Statistical methods in modeling disease surveillance data with misclassification, Yaxuan Sun

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Nonparametric regression models with and without measurement error in the covariates, for univariate and vector responses: a Bayesian approach, Eduardo Antonio Trujillo-Rivera

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Graphical discovery in stochastic actor-oriented models for social network analysis, Samantha Carroll Tyner

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Exploring dependence in binary Markov random field models, Kenneth William Wakeland

Theses/Dissertations from 2016

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Kernel deconvolution density estimation, Guillermo Basulto-Elias

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Bayesian contributions to the modeling of multivariate macroeconomic data, Lendie Ruth Follett

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Topics in empirical Bayesian analysis, Robert Christian Foster

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Evaluation of Parametric and Nonparametric Statistical Methods in Genomic Prediction, Reka Howard

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High-dimensional hierarchical models and massively parallel computing, William Michael Landau

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Statistical methods in sports with a focus on win probability and performance evaluation, Dennis Lock

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Bayesian models and inferential methods for forecasting disease outbreak severity, Nicholas Lorenz Michaud

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Interfacing R with Web Technologies for Interactive Statistical Graphics and Computing with Data, Carson Sievert

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Selected topics in measurement error and functional data analysis, Yuhang Xu

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Probabilistic methods for quality improvement in high-throughput sequencing data, Xin Yin

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Inference based on data from superpositions of identical renewal processes, Wei Zhang

Theses/Dissertations from 2015

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Interactive visualization for missing values, time series, and areal data, Xiaoyue Cheng

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Small area prediction based on unit level models when the covariate mean is measured with error, Andreea Luisa Erciulescu

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Contributions to modeling spatially indexed functional data using a reproducing kernel Hilbert space framework, Daniel Clayton Fortin

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Some methods for handling missing data in surveys, Jongho Im

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Local prediction and classification techniques for machine learning and data mining, Cory Lee Lanker

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Statistical methods in detecting differential expressed genes, analyzing insertion tolerance for genes and group selection for survival data, Fangfang Liu

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Experimental designs for multiple responses with different models, Wilmina Mary Marget

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Applications of technology and large data in statistics education and statistical graphics, Karsten Tait Maurer

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Applications of and extensions to state-space models, David Allen Osthus

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Computer model optimization within hidden constraints, Jostein Reiners

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Bayesian modeling and computation with latent variables, Matthew Wayne Simpson

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Perception in statistical graphics, Susan Ruth VanderPlas

Theses/Dissertations from 2014

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An investigation of viral fitness using statistical and computer models of Equine Infectious Anemia Virus infection, Derek Blythe

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A local structure graph model for network analysis, Emily Taylor Casleton

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Imputation of missing values using quantile regression, Senniang Chen

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Modeling, inference and clustering for equivalence classes of 3-D orientations, Chuanlong Du

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Mixed effects modeling with missing data using quantile regression and joint modeling, Luke Karsten Fostvedt

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Characterizing diurnal and interannual variability in the atmosphere through physical and stochastic models, Jonathan Michael Hobbs

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Contributions to the design and analysis of nondestructive evaluation experiments, Yew-Meng Koh

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Biclustering methods and a Bayesian approach to fitting Boltzmann machines in statistical learning, Jing Li

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Inference for High-Dimensional Covariance Matrices and Thresholding Tests for High-Dimensional Count Distributions, Yumou Qiu

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Explorations of the lineup protocol for visual inference: application to high dimension, low sample size problems and metrics to assess the quality, Niladri Roy Chowdhury

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Topics in cancer genomics, Sachet Ashok Shukla

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Statistical methods for random rotations, Bryan Stanfill

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On empirical likelihood methods for irregularly located spatial data, Matthew Van Hala

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Estimation Under Stochastic Differential Equations, Shan Yang