Probability Matching Priors: Higher Order Asymptotics артикул 3164e.
Probability Matching Priors: Higher Order Asymptotics артикул 3164e.

Book DescriptionProbability 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 озыдп 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 .  Clatron2004 г ISBN 038720329X.