Archive for the ‘MDL’ Category

Inference after eliminating Bayesian models of excessive codelength

1 November 2017 Comments off

“The maximum-entropy and minimax redundancy distribution classes of sufficiently small codelength”

10th Workshop on Information Theoretic Methods in Science and Engineering

Paris, France

September 11, 2017

David R. Bickel

University of Ottawa

A Bayesian approach to informing decision makers

23 September 2016 Comments off

Profile likelihood & MDL for measuring the strength of evidence

8 April 2013 Comments off

Estimates of the local FDR

13 February 2013 Comments off

Z. Yang, Z. Li, and D. R. Bickel, “Empirical Bayes estimation of posterior probabilities of enrichment: A comparative study of five estimators of the local false discovery rate,” BMC Bioinformatics 14, art. 87 (2013). published version |  2011 version | 2010 version


This paper adapts novel empirical Bayes methods for the problem of detecting enrichment in the form of differential representation of genes associated with a biological category with respect to a list of genes identified as differentially expressed. Read more…

Optimal strength of evidence

13 February 2013 Comments off

D. R. Bickel, “Minimax-optimal strength of statistical evidence for a composite alternative hypothesis,” International Statistical Review 81, 188-206 (2013). 2011 version | Simple explanation (added 2 July 2017)


This publication generalizes the likelihood measure of evidential support for a hypothesis with the help of tools originally developed by information theorists for minimizing the number of letters in a message. The approach is illustrated with an application to proteomics data.

MLE of the local FDR

13 February 2013 Comments off

Y. Yang, F. A. Aghababazadeh, and D. R. Bickel, “Parametric estimation of the local false discovery rate for identifying genetic associations,” IEEE/ACM Transactions on Computational Biology and Bioinformatics 10, 98-108 (2013). 2010 version | Slides


Read more…

Local FDR estimation for low-dimensional data

18 October 2012 Comments off

M. Padilla and D. R. Bickel, “Estimators of the local false discovery rate designed for small numbers of tests,” Statistical Applications in Genetics and Molecular Biology 11 (5), art. 4 (2012). Full article | 2010 & 2012 preprints


This article describes estimators of local false discovery rates, compares their biases for small-scale inference, and illustrates the methods using a quantitative proteomics data set. In addition, theoretical results are presented in the appendices.