Zhengyuan Zhu : High Order Laplace Approximation for Design and Statistical Inference of Dependent Data

Posted by , part of the Statistics and Data Science Seminar.

At

March 16, 2011, 3 p.m.

In

SEO 636

Abstract

Laplace approximation has been used in many statistical applications to approximate integrals. In this talk we present several applications which use high order Laplace approximation to derive theoretical results and develop efficient algorithms, including construction of prediction interval which has zero second order coverage probability bias, design criteria for prediction with estimated covariance parameters, theoretical comparison of predictive densities for dependent observations, and approximate inference for spatial generalized linear mixed models.