Document Type
Article
Language
eng
Format of Original
11 p.
Publication Date
9-2013
Publisher
Elsevier
Source Publication
Journal of Multivariate Analysis
Source ISSN
0047-259X
Original Item ID
doi: 10.1016/j.jmva.2013.05.012
Abstract
A multiple hypothesis problem with directional alternatives is considered in a decision theoretic framework. Skewness in the alternatives is considered, and it is shown that this skewness permits the Bayes rules to possess certain advantages when one direction of the alternatives is more important or more probable than the other direction. Bayes rules subject to constraints on certain directional false discovery rates are obtained, and their performances are compared with a traditional FDR rule through simulation. We also analyzed a gene expression data using our methodology, and compare the results to that of a FDR method.
Recommended Citation
Bansal, Naveen K. and Miescke, Klaus J., "Bayesian Decision Theoretic Approach to Directional Multiple Hypotheses Problems" (2013). Mathematics, Statistics and Computer Science Faculty Research and Publications. 196.
https://epublications.marquette.edu/mscs_fac/196
Comments
Accepted version. Journal of Multivariate Analysis, Vol. 120 (September 2013): 205-215. DOI.
NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Multivariate Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Multivariate Analysis, [VOL 120, (September 2013)] DOI.