Neyman Seminar: On shrinkage priors in high-dimensions

Neyman Seminar: On shrinkage priors in high-dimensions

Neyman Seminar
Feb 4, 2015, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Debdeep Pati, Department of Statistics, Florida State University
Shrinkage priors are routinely used as alternative to point-mass mixture priors for sparse modeling in high-dimensional applications. The question of statistical optimality in such settings is under-studied in a Bayesian framework. We provide theoretical understanding of such Bayesian procedures in terms of two key phenomena: prior concentration around sparse vectors and posterior...