Bayesian variable selection in clustering via dirichlet process mixture models

Bayesian variable selection in clustering via dirichlet process mixture models

The increased collection of high-dimensional data in various fields has raised a strong interest in clustering algorithms and variable selection procedures. In this disserta- tion, I propose a model-based method that addresses the two problems simultane- ously. I use Dirichlet process mixture models...

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Bibliographic Details
Main Author: Kim, Sinae
Other Authors: Vannucci, Marina
Format: Others
Language:en_US
Published: Texas A&M University 2007
Subjects:
Bayesian inference
Clustering
Dirichlet process mixture model
DNA microarray data analysis
variable selection
wavelet shrinkage
Online Access:http://hdl.handle.net/1969.1/5888

Internet

http://hdl.handle.net/1969.1/5888

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