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1.
Bayesian Nonparametric Methods for Analysis of Electronic Health Records
by Xu, Dandan, Ph.D.  University of Florida. 2016: 108 pages; 10679207.
3.
Objective Bayesian inference for stress-strength models and Bayesian ANOVA
by Min, Xiaoyi, Ph.D.  University of Missouri - Columbia. 2012: 128 pages; 3537873.
4.
Applications of Genomic Resources and Bayesian Inference Methods to the Breeding of Peach [Prunus persica (L.) Batsch]
by Fresnedo Ramirez, Jonathan, Ph.D.  University of California, Davis. 2014: 168 pages; 3646288.
5.
Synthesizing multiple data sources to understand the population and community ecology of California trees
by Solera, Melissa Viola Eitzel, Ph.D.  University of California, Berkeley. 2014: 175 pages; 3686015.
6.
Detection and explanation of statistical differences across a pair of groups
by Sverchkov, Yuriy, Ph.D.  University of Pittsburgh. 2014: 159 pages; 3647988.
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Slope estimation in a parametric measurement error model: A simulation study
by Lu, Hui, M.S.  The University of Texas School of Public Health. 2011: 38 pages; 1502170.
9.
Parallel Junction Tree Algorithm on GPU
by Zheng, Lu, Ph.D.  Carnegie Mellon University. 2013: 94 pages; 3575068.
10.
Classification accuracy of logistic regression models under misspecifications
by Zhang, Enhan, Ph.D.  New York University. 2014: 137 pages; 3635317.
11.
Statistical methods for research in healthcare quality and safety from observational data
by Myers, Jessica, Ph.D.  The Johns Hopkins University. 2010: 113 pages; 3428625.
13.
Controlling with Model Trees
by Kemerling, Robert Alan, Ph.D.  Nova Southeastern University. 2011: 121 pages; 3478677.
15.
Bayesian lasso: An extension for genome-wide association study
by Joo, LiJin, Ph.D.  New York University. 2017: 119 pages; 10243856.
16.
Bayesian mortgage default models
by Xu, Feng, Ph.D.  The George Washington University. 2008: 157 pages; 3316109.
18.
Optimal Seed Deployment under Climate Change using Spatial Models and Prediction of Genetic Merit in Loblolly Pine
by Farjat, Alfredo Ezequiel, Ph.D.  North Carolina State University. 2015: 171 pages; 10585497.
20.
Refined-scale crash data analysis using multi-level regression models
by Ma, Xiaoxiang, Ph.D.  Colorado State University. 2016: 175 pages; 10240737.
21.
Heterogeneous Treatment Effect Estimation Using Machine Learning
by Kuenzel, Soeren R., Ph.D.  University of California, Berkeley. 2019: 177 pages; 13903254.
22.
Effects of aluminum and iron nanoparticle additives on composite AP/HTPB solid propellant regression rate
by Styborski, Jeremy A., M.S.  Rensselaer Polytechnic Institute. 2014: 40 pages; 1561975.
23.
Optimal designs for segmented polynomial regression models and web-based implementation of optimal design software
by Wu, XiangFeng, Ph.D.  State University of New York at Stony Brook. 2007: 81 pages; 3337619.
25.
A new approach of top -down induction of decision trees for knowledge discovery
by Lee, Jun-Youl, Ph.D.  Iowa State University. 2008: 186 pages; 3307038.
26.
Roughened Random Forests for Binary Classification
by Xiong, Kuangnan, Ph.D.  State University of New York at Albany. 2014: 136 pages; 3624962.
27.
Associating single nucleotide polymorphisms (SNPs) with binary traits
by Lipka, Alexander E., Ph.D.  Purdue University. 2009: 108 pages; 3403170.
29.
A Crash Risk Index for Freeways Based on Crash Risk Prediction Models and Its Applications
by Chang, Hyoseuk, Ph.D.  University of Maryland, College Park. 2018: 160 pages; 10839822.
30.
Integrating Exponential Dispersion Models to Latent Structures
by Basbug, Mehmet Emin, Ph.D.  Princeton University. 2017: 125 pages; 10254057.
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