The articles of this volume will not be indexed individually. It contains the following papers:
Colin McCulloch, Jacob Laading, Alyson Wilson, and Valen Johnson, A shape-based framework for automated image segmentation; Mithat Gönen and Peter H. Westfall, Bayes factors for variance components; Lawrence Marsh and Arnold Zellner, Bayesian solutions to a class of selection problems; Giovanni Petris, Bayesian spectral analysis of long memory time series; F. Jay Breidt and Alicia L. Carriquiry, Bayesian estimation of genetic trends; C. S. Wang, R. L. Quaas, and E. J. Pollak, Bayesian analysis of calving ease scores and birth weights; Giulianella Coletti, Updating and Extension of coherent conditional probabilities; Giulio D’Agostini, A theory of measurement uncertainty based on conditional probability; Frank Lad, Three useful applications of conditional probability, understood as an assertion of uncertain knowledge; Jose Mario Quintana and Bluford H. Putnam, Debating currency markets efficiency using dynamic multiple-factor models; Elizabeth R. DeLong, Charlotte L. Nelson, John B. Wong, Stephen G. Pauker and David B. Pryor, The ischemic heart disease port as related to guideline development; Getachew Asfaw Dagne and S. James Press, Robustness of the directional neighborhoods approach to image classification with respect to spatial correlation; John F. Shortle and Max B. Mendel, Probabilistic design of rotors: minimizing imbalance; Nozer Singpurwalla and Joseph N. Skwish, Data fusion and maintenance policies for continuous production processes; Michael K. Pitt and Neil Shephard, Antithetic variables for MCMC methods applied to non-gaussian state space models; William Griffiths, Tim Coelli, and Graeme Thomson, Predicting a product from seemingly unrelated regressions; Julene Kemp, J. L. Madrigal, and Del T. Scott, An examination of pairwise comparison using the dynamic linear model for unbalanced data; Ming-Hui Chen, Markov chain Monte Carlo sampling for evaluating multidimensional integrals. With application to Bayesian computation; Woollcott Smith, Andrew R. Solow, and Peter E. Preston, A Bayes approach to the species overlap problem; Andrew R. Solow, Bayesian methods for inference about extinction times; Fabrizio Ruggeri and Brani Vidakovic, A Bayesian decision theoretic approach to wavelet thresholding: scale parameter models; Omar Aguilar, Wavelet and autoregressive decomposition for evaluating frequency composition in time series; Marina Vannucci and Fabio Corradi, Model shrinking of wavelet coefficients and applications; Maurits Malfait, Maarten Jansen and Dirk Roose, Bayesian approach to wavelet-based image processing; Richard J. Patz, Markov chain Monte Carlo methods for incomplete, multiple item type educational assessment data; J. Alex Stark and William J. Fitzgerald, Matrix gyrations and model selection; Bradley P. Carlin, Lance A. Waller Hong Xia and Alan E. Gelfand, Spatio-temporal hierarchical modeling of disease rates; Christoper H. Schmid and Emery N. Brown, A hierarchical Bayes model for human growth; P. K. Vlachos and A. E. Gelfand, Design of group sequential clinical trials: A Bayesian decision theoretic approach; Mary Kathryn Cowles, Bayesian joint accelerated failure time models for surrogate markers and survival time; Judea Pearl, Covariate selection: A simple solution to a long-standing problem; R. Todd Ogden, Wavelets in Bayesian change-point analysis; Lynn Kuo and Bani Mallick, Bayesian variable selection for regression models; Jacinto Martín, David Ríos Insua and Fabrizio Ruggeri, Checking dominance for several classes of loss functions; Richard Simon and Laurence S. Freedman, Bayesian design and analysis of 2 by 2 factorial clinical trials; Balakrishna Hosmane, Kannan Natarajan, and Guoliang Cao, Bayesian inference for dose-response model with dependent binary data; Getachew Asfaw Dagne and S. James Press, Bayesian predication for small areas using SUR models; Marianna Pensky, A wavelet approach to nonparametric empirical Bayes estimation; Michael Smith and Robert Kohn, Bayesian robust nonparametric regression; Zvi Covaliu and Refik Soyer, Bayesian project management; Hugo A. Keuzenkamp and Michael McAleer, The complexity of simplicity; L. Mark Berliner, Simplicity and complexity in scientific models; R. Carter and A. Zellner, The ARAR model for time series; Gary Koop and Herman K. van Dijk, Testing for integration using evolving trend models; Kajal Lahiri and Manimoy Paul, Relative performance of pre-test estimators in the presence of a unit root; John G. Wilson and Elmira Popova, Bayesian approaches to maintenance intervention; William Griffiths and Rebecca Valenzuela, Bayesian estimation of a linear expenditure system with some zero expenditures; Thomas Heckelei, Ron C. Mittelhammer and Thomas I. Wahl, Evaluation of equality and inequality restrictions for a meat demand system: A robust Bayesian bootstrap approach; Sergio Lence and Douglas Miller, Estimation of multi-output production functions without activity-specific input data; Garth J. Holloway, Frank M. Han and T. J. Wyatt, Inferences about the farm problem in a non-nested, switching-regression framework; Jeffrey H. Dorfman, A new approach to composite qualitative forecasting; Tim Swartz, Bayesian goodness-of-fit; Arkady Shemyakin, Sensitivity of a Markowitz type model to Bayesian inputs; Bruno Betrò, Alessandra Guglielmi and Francesca Rossi, Robust Bayesian analysis for the power law process; Yeu-Shiang Huang and Vicki M. Bier, Natural conjugate prior distributions for nonhomogeneous Poisson processes; Woojune Yi and Vicki M. Bier, \(n\)-dimensional prior distributions with arbitrary marginal distributions and correlation coefficients; Eric T. Bradlow and Alan M. Zaslavsky, Case influence analysis in Bayesian inference; Cinzia Carota, Mixtures of Dirichlet processes according to a Dirichlet process; Amos Golan and George Judge, A simultaneous estimation and variable selection rule using a generalized maximum entropy estimator; Minoru Hayashida, Forecasting growth rates of gross city products in Japan using Bayesian shrinkage ABIC and Gibbs sampler; Thomas J. Jiang, Bayesian method for informatively censored categorical data; Frank Lad, What should we teach students of mathematical statistics about probability?; Dale J. Poirier, Local Bayes factor approximations; David Ríos Insua, Fabrizio Ruggeri and Michael Wiper, Bayesian analysis of some queues; Teruo Nakatsuma and Hiroki Tsurumi, ARMA-GARCH models: Bayes estimation versus MLE, and Bayes non-stationarity test.