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Adjusted Bayesian inference for selected parameters

Seminar | September 10 | 4-5 p.m. | 1011 Evans Hall

Speaker: Daniel Yekutieli, Professor, Department of Statistics and Operations Research, Tel Aviv University

Sponsor: Statistics, Department of

I will address the problem of providing inference for parameters selected after viewing the data. A frequentist solution to this problem is using False Discovery Rate controlling multiple testing procedures to select the parameters and constructing False Coverage-statement Rate adjusted confidence intervals for the selected parameters.I will argue that selection also affects Bayesian inference and present a Bayesian framework for providing inference for selected parameters. I will explain the role of selection in controlling the occurrence of false discoveries in Bayesian analysis and demonstrate how to specify selection criteria. I will also explain the relation between our Bayesian approach and the Bayesian FDR approach and apply it to microarray data.

Event Contact: 510-642-2781