Bayesian Methods Under Unknown Prior Distributions with Applications to The Analysis of Gene Expression Data

Bayesian Methods Under Unknown Prior Distributions with Applications to The Analysis of Gene Expression Data

The local false discovery rate (LFDR) is one of many existing statistical methods that analyze multiple hypothesis testing. As a Bayesian quantity, the LFDR is based on the prior probability of the null hypothesis and a mixture distribution of null and non-null hypothesis. In practice, the LFDR is u...

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Bibliographic Details
Main Author: Rahal, Abbas
Other Authors: Bickel, David
Format: Others
Language:en
Published: Université d'Ottawa / University of Ottawa 2021
Subjects:
Robust Bayesian statistics
Imprecise probability
Bayesian model checking
Blended inference
Posterior predictive p-value
Local false discovery rate
Empirical Bayes
Multiple testing
Bayesian false discovery rate
Measure of evidence
Direct likelihood inference
Likelihoodism
Online Access:http://hdl.handle.net/10393/42408
http://dx.doi.org/10.20381/ruor-26628

Internet

http://hdl.handle.net/10393/42408
http://dx.doi.org/10.20381/ruor-26628

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