The field of statistics has undergone rapid and widespread development during the past two decades, and the Bayesian approach to statistics has provided both a general framework and a creative stimulus for all aspects of this development. Research in Bayesian statistics has had an effect on the foundations of statistical inference and probability, statistical theory and methodology, and the applications of statistics in various fields. Since their inception in 1979, the Valencia International Meetings on Bayesian Statistics, held in Spain every four years, have been the main source of information about the current state of statistical knowledge and research. This volume contains all papers presented at the most recent conference.

Table of Contents:
Part 1 Invited papers: de Finetti's approach to group decision making; the future of statistics - teaching and research; gaining weight - a Bayesian approach; ranges of posterior probablities for unimodal priors with specified quantiles; a Bayesian analysis of simple mixture problems; multiple comparisons, multiple tests and data dredging; the infinite regress and its conjugate analysis; recent progress on de Finetti's notions of exchangeability; a Bayesian model and a graphical elicitation procedure for multiple comparisons; the future of statistics in retrospect; experiments in Bayesian image analysis; software for Bayesian analysis - current status and additional needs; the data trajectory; de Finetti's theorem, induction and A(n) or Bayesian nonparametric predictive inference; Bayesian palaeoethnobotany; asymptotics in Bayesian computation; stochastic models of incarceration careers; statistical inference concerning Hardy-Weinberg equilibrium; approximating posterior distributions; modelling with heavy tails; on being imprecise at the higher levels of a hierarchical linear model; robust Bayesian analysis in hierarchical models; using the SIR algorithm to simulate posterior distributions; robustness in generalized ridge regression and related topics; aspects of numerical integration and summarization; what should be Bayesian about Bayesian software?; to weight or not to weight, that is the question; Bayesian approaches to clinical trials; partial and interaction spline models; modelling expert opinion; a Bayesian era. Part 2 Contributed papers: Bayesian estimation of Poisson means, using a hierarchical log-linear model; Bayesian analysis of a pure birth process with linear birth rate; Bayesian regression analysis under non-normal errors; on Kolmogorov's partial sufficiency; invariance and Bayesian predictive analysis with an application to diallel cross design; on differentiability properties of Bayes operators; parametric estimation with distance; choosing a quality supplier, a Bayesian approach; global versus local screening; estimated public welfare quality control - error rates and penalties; iterative procedures for continuous Bayesian designs; a report on continuity of uncertainty functions; a Bayesian approach to the analysis of LD50 experiments; outliers and influence - evaluation by posteriors of parameters in the linear model; combining opinions in a predictive case; Bayesian estimation of the variance components in a general random linear model; a heteroscedastic hierarchical model; algorithmic diagnosis of appendicitis using Bayes' theorem and logistic regression; prior and posterior tail comparisons. (Part contents)