By Richard W. Andrews, James O. Berger, Murray H. Smith (auth.), Constantine Gatsonis, James S. Hodges, Robert E. Kass, Nozer D. Singpurwalla (eds.)
The prior few years have witnessed dramatic advances in computational equipment for Bayesian inference. consequently, Bayesian techniques to fixing a wide selection of difficulties in facts research and decision-making became possible, and there's presently a development spurt within the program of Bayesian equipment. the aim of this quantity is to offer a number of targeted examples of purposes of Bayesian pondering, with an emphasis at the medical or technological context of the matter being solved. The papers accumulated the following have been awarded and mentioned at a Workshop held at Carnegie-Mellon collage, September 29 via October 1, 1991. There are 5 ma jor articles, every one with dialogue items and a answer. those articles have been invited via us following a public solicitation of abstracts. the issues they handle are assorted, yet all undergo on coverage decision-making. even though no longer a part of our unique layout for the Workshop, that commonality of topic does emphasize the usefulness of Bayesian meth ods during this area. besides the invited papers have been numerous extra commentaries of a basic nature; the 1st remark used to be invited and the rest grew out of the dialogue on the Workshop. additionally there are 9 contributed papers, chosen from the thirty-four offered on the Workshop, on numerous purposes. This selection of case reviews illustrates the ways that Bayesian tools are being included into statistical perform. The strengths (and obstacles) of the strategy turn into obvious throughout the examples.