Articles liés à Probability Matching Priors: Higher Order Asymptotics

Probability Matching Priors: Higher Order Asymptotics - Couverture souple

Livre 25 sur 72: Lecture Notes in Statistics

Datta, Gauri Sankar; Mukerjee, Rahul

 
9780387203294: Probability Matching Priors: Higher Order Asymptotics

Synopsis

This is the first book on the topic of probability matching priors. The topic has been of substantial current interest with articles in top journals. This book will be the only source covering the most important developments in this area in a single volume.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de la quatrième de couverture

Probability matching priors, ensuring frequentist validity of posterior credible sets up to the desired order of asymptotics, are of substantial current interest. They can form the basis of an objective Bayesian analysis. In addition, they provide a route for obtaining accurate frequentist confidence sets, which are meaningful also to a Bayesian. This monograph presents, for the first time in book form, an up-to-date and comprehensive account of probability matching priors addressing the problems of both estimation and prediction. Apart from being useful to researchers, it can be the core of a one-semester graduate course in Bayesian asymptotics.

Gauri Sankar Datta is a professor of statistics at the University of Georgia. He has published extensively in the fields of Bayesian analysis, likelihood inference, survey sampling, and multivariate analysis.

Rahul Mukerjee is a professor of statistics at the Indian Institute of Management Calcutta. He co-authored three other research monographs, including A Calculus for Factorial Arrangements in this series. A fellow of the Institute of Mathematical Statistics, Dr. Mukerjee is on the editorial boards of several international journals.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.