This paper reviews recent developments in higher-order asymptotics for marginal posterior distributions, and related quantities, for practical use in Bayesian analysis. In this respect, we outline how modern asymptotic theory, which provides accurate inferences in a variety of parametric statistical problems even for small sample sizes, may routinely be applied in practice. The focus is on default Bayesian inference in the presence of nuisance parameters
Higher-order asymptotics in Bayesian inference
VENTURA, LAURA;
2012
Abstract
This paper reviews recent developments in higher-order asymptotics for marginal posterior distributions, and related quantities, for practical use in Bayesian analysis. In this respect, we outline how modern asymptotic theory, which provides accurate inferences in a variety of parametric statistical problems even for small sample sizes, may routinely be applied in practice. The focus is on default Bayesian inference in the presence of nuisance parametersFile in questo prodotto:
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