Bayesian models for DNA microarray data analysis /

Selection of significant genes via expression patterns is important in a microarray problem. Owing to small sample size and large number of variables (genes), the selection process can be unstable. This research proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent v...

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Bibliographic Details

Main Author:	Lee, Kyeong Eun, 1971-
Other Authors:	Mallick, Bani K. (Thesis advisor), Calvin, James A. (Thesis advisor)
Format:	Thesis eBook
Language:	English
Published:	[College Station, Tex.] : [Texas A&M University], [2005]
Subjects:	Major statistics. Cox's Proportional Hazard Model Probit Regression Model Weibull Regression Model Wavelet DNA microarray Mixture of Dirichlet Processes Curve Clustering Bayesian Variable Selection Survival Analysis
Online Access:	Link to OAK Trust copy