c2377c0412c24410VgnVCM100000c2b1d38dRCRDapproved/UMICH/stats/Home/News & Events/Statistics SeminarDepartment Seminar Series: Nicholas Polson, Recursive Bayesian Computation###@###(Fri, 11 Apr 2014)Department Seminar Series: Nicholas Polson, Recursive Bayesian Computation###@###(Fri, 11 Apr 2014)340 West Hallstats1397230200000139723020000011:30 AM<p>Abstract: &nbsp;In this paper we develop a framework for recursive Bayesian computation. By exploiting an auxiliary latent variable structure we provide sequential parameter learning for a wide class of models. We illustrate our methodology with applications to high dimensional sparse regression, dynamic logistic classification, mixture Kalman filters and nonlinear and non-Gaussian state space models. The methods developed here are available in the package ParticleBayes.R.</p>Nlorieannbzuniga139627799871792377c0412c24410VgnVCM100000c2b1d38d____once11112newnewNicholas Polson, PhD., Professor of Econometrics and Statistics, University of Chicago Booth School of Businesshttp://faculty.chicagobooth.edu/nicholas.polson/index.html