VOL. 19 · NO. 1 | February 2004
 
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Frontmatter
Statist. Sci. 19 (1), (February 2004)
No abstract available
Statist. Sci. 19 (1), (February 2004)
No abstract available
Reviews
Christian P. Robert, George Casella
Statist. Sci. 19 (1), 1-2, (February 2004) DOI: 10.1214/088342304000000062
No abstract available
Then
D. R. Bellhouse
Statist. Sci. 19 (1), 3-43, (February 2004) DOI: 10.1214/088342304000000189
Now
A. P. Dawid
Statist. Sci. 19 (1), 44-57, (February 2004) DOI: 10.1214/088342304000000125
KEYWORDS: Borel criterion, Calibration, falsification, Jeffreys’s law
M. J. Bayarri, J. O. Berger
Statist. Sci. 19 (1), 58-80, (February 2004) DOI: 10.1214/088342304000000116
KEYWORDS: Admissibility, Bayesian model checking, conditional frequentist, confidence intervals, consistency, coverage, design, hierarchical models, nonparametric Bayes, objective Bayesian methods, P-values, reference priors, testing
Merlise Clyde, Edward I. George
Statist. Sci. 19 (1), 81-94, (February 2004) DOI: 10.1214/088342304000000035
KEYWORDS: Bayes factors, classification and regression trees, model averaging, linear and nonparametric regression, objective prior distributions, reversible jump Markov chain Monte Carlo, Variable selection
Peter Müller, Fernando A. Quintana
Statist. Sci. 19 (1), 95-110, (February 2004) DOI: 10.1214/088342304000000017
KEYWORDS: Dirichlet process, regression, Density estimation, Survival analysis, Pólya tree, random probability model (RPM)
Stephen G. Walker
Statist. Sci. 19 (1), 111-117, (February 2004) DOI: 10.1214/088342304000000134
KEYWORDS: Bayes factor, Bayes nonparametrics, consistency, Hellinger distance
C. Andrieu, A. Doucet, C. P. Robert
Statist. Sci. 19 (1), 118-127, (February 2004) DOI: 10.1214/088342304000000071
KEYWORDS: Monte Carlo methods, importance sampling, Markov chain Monte Carlo (MCMC) algorithms
D. M. Titterington
Statist. Sci. 19 (1), 128-139, (February 2004) DOI: 10.1214/088342304000000099
KEYWORDS: Bayesian methods, Bayesian model choice, feed-forward neural network, Graphical model, Laplace approximation, machine learning, Markov chain Monte Carlo, variational approximation
Michael I. Jordan
Statist. Sci. 19 (1), 140-155, (February 2004) DOI: 10.1214/088342304000000026
KEYWORDS: probabilistic graphical models, junction tree algorithm, sum-product algorithm, Markov chain Monte Carlo, variational inference, Bioinformatics, error-control coding
David J. Spiegelhalter
Statist. Sci. 19 (1), 156-174, (February 2004) DOI: 10.1214/088342304000000080
KEYWORDS: Bayes theorem, Prior distributions, sceptical prior distribution, data monitoring committee, cost-effectiveness analysis, historical data, decision theory
Donald A. Berry
Statist. Sci. 19 (1), 175-187, (February 2004) DOI: 10.1214/088342304000000044
KEYWORDS: Bayesian updating, decision analysis, predictive probabilities, Clinical trials, Adaptive designs, clinical ethics, auxiliary endpoints, extraim analyses
Shane T. Jensen, X. Shirley Liu, Qing Zhou, Jun S. Liu
Statist. Sci. 19 (1), 188-204, (February 2004) DOI: 10.1214/088342304000000107
KEYWORDS: Gene regulation, motif discovery, Bayesian models, scoring functions, optimization, Markov chain Monte Carlo
Robert L. Wolpert
Statist. Sci. 19 (1), 205-218, (February 2004) DOI: 10.1214/088342304000000053
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