Bayesian Model Selection for High-dimensional High-throughput Data

Bayesian Model Selection for High-dimensional High-throughput Data

Bayesian methods are often criticized on the grounds of subjectivity. Furthermore, misspecified priors can have a deleterious effect on Bayesian inference. Noting that model selection is effectively a test of many hypotheses, Dr. Valen E. Johnson sought to eliminate the need of prior specification b...

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Bibliographic Details
Main Author: Joshi, Adarsh
Other Authors: Johnson, Valen E.
Format: Others
Language:en_US
Published: 2012
Subjects:
Bayes factors
Bayes factors based on test statistics
Bayesian Graphs
MCMC
Objective Bayesian Analysis
Bayesian Model Selection
Microarray data
Single-nucleotide polymorphism (SNP) data
Online Access:http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7740

Internet

http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7740

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