Document Type

Article

Language

eng

Publication Date

2017

Publisher

InTech

Source Publication

Bayesian Inference

Source ISSN

978-953-51-3577-7

Abstract

For high-dimensional hypothesis problems, new approaches have emerged since the publication. The most promising of them uses Bayesian approach. In this chapter, we review some of the past approaches applicable to only law-dimensional hypotheses testing and contrast it with the modern approaches of high-dimensional hypotheses testing. We review some of the new results based on Bayesian decision theory and show how Bayesian approach can be used to accommodate directional hypotheses testing and skewness in the alternatives. A real example of gene expression data is used to demonstrate a Bayesian decision theoretic approach to directional hypotheses testing with skewed alternatives.

Comments

Published version. Bayesian Inference, (2017): 63-75. DOI. © 2017 InTech. Used with permission.

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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