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INVITED PAPERS with discussion
An extended maximum entropy principle and a Bayesian
H and Eriksson E A Probability forecasting stochastic
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A.F.M. Smith Aitchison Amer applications approximation assessment assume assumption Bayes Bayes factor Bayesian analysis Bayesian approach Bayesian inference Bayesian statistics beliefs binomial calibration coefficients coherence components conditional conjugate prior consider corresponding covariance matrix decision maker decision problem defined denote depend diagnostic discussion Econometrics error estimate evaluation example expected exponential family factor finite forecaster Geisser given important independent integration J.M. Bernardo likelihood function likelihood principle Lindley linear models mathematical maximum entropy measure median methods mixture mode Monte Carlo North-Holland nuclear observations obtained opinion optimal outliers paper possible posterior density posterior distribution posterior mean posterior probability predictive distribution prevision principle prior distribution prior information probability distribution procedure Professor random variable reasons regression sample Section simple specification standard structure subjective probability Suppose Theorem theory transformation treatment University utility function vague prior Valencia values variance vector weight of evidence well-calibrated