Relevant statistics for Bayesian model choice
نویسندگان
چکیده
منابع مشابه
Relevant statistics for Bayesian model choice
The choice of the summary statistics in Bayesian inference and in particular in ABC algorithms is paramount to produce a valid outcome. We derive necessary and sufficient conditions on those statistics for the corresponding Bayes factor to be convergent, namely to asymptotically select the true model. Those conditions, which amount to the expectations of the summary statistics to asymptotically...
متن کاملBayesian Logistic Regression Model Choice via Laplace-Metropolis Algorithm
Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...
متن کاملBayesian Inference for Model Choice
Two nested or non-nested candidate sampling models for an observed data set may be compared by consideration of summaries of a probability plot, which contrasts the posterior quantiles of the log-likelihoods under the two models. The procedures address both preference inference and refutation inference, and extensions to DIC and alternatives to AIC are developed. Preference inference favors mod...
متن کاملComparison of Estimates Using Record Statistics from Lomax Model: Bayesian and Non Bayesian Approaches
This paper address the problem of Bayesian estimation of the parameters, reliability and hazard function in the context of record statistics values from the two-parameter Lomax distribution. The ML and the Bayes estimates based on records are derived for the two unknown parameters and the survival time parameters, reliability and hazard functions. The Bayes estimates are obtained based on conju...
متن کاملBayesian Statistics BAYESIAN STATISTICS ∗
Mathematical statistics uses two major paradigms, conventional (or frequentist), and Bayesian. Bayesian methods provide a complete paradigm for both statistical inference and decision making under uncertainty. Bayesian methods may be derived from an axiomatic system, and hence provide a general, coherent methodology. Bayesian methods contain as particular cases many of the more often used frequ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series B (Statistical Methodology)
سال: 2013
ISSN: 1369-7412
DOI: 10.1111/rssb.12056