A Bayesian decision theoretic approach to directional multiple hypotheses problems
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 o...
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| Published in | Journal of multivariate analysis Vol. 120; pp. 205 - 215 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Elsevier Inc
01.09.2013
Taylor & Francis LLC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0047-259X 1095-7243 |
| DOI | 10.1016/j.jmva.2013.05.012 |
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| 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. |
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| AbstractList | 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. 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. [PUBLICATION ABSTRACT] |
| Author | Bansal, Naveen K. Miescke, Klaus J. |
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| Cites_doi | 10.1016/j.jspi.2010.03.013 10.1214/aoms/1177707034 10.1038/nature03315 10.1016/j.jspi.2003.07.020 10.1016/j.jspi.2007.01.006 10.1093/oso/9780198506508.001.0001 10.1037/1082-989X.7.3.356 10.1111/j.2517-6161.1995.tb02031.x 10.1126/science.1085242 10.1214/aoms/1177706873 10.1586/ehm.12.54 |
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| Keywords | 62H15 MicroRNA 62C10 False discovery rate Microarray data analysis Multiple hypotheses Directional alternatives |
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| SubjectTerms | Bayesian analysis Decision theory Directional alternatives False discovery rate Gene expression Hypotheses Mathematical problems Microarray data analysis MicroRNA Multiple hypotheses Statistical methods Studies |
| Title | A Bayesian decision theoretic approach to directional multiple hypotheses problems |
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