An overview of robust Bayesian analysis
Robust Bayesian analysis is the study of the sensitivity of Bayesian answers to uncertain
inputs. This paper seeks to provide an overview of the subject, one that is accessible to …
inputs. This paper seeks to provide an overview of the subject, one that is accessible to …
[图书][B] The Bayesian choice: from decision-theoretic foundations to computational implementation
CP Robert - 2007 - Springer
This paperback edition, a reprint of the 2001 edition, is a graduate-level textbook that
introduces Bayesian statistics and decision theory. It covers both the basic ideas of statistical …
introduces Bayesian statistics and decision theory. It covers both the basic ideas of statistical …
[图书][B] An introduction to Bayesian analysis: theory and methods
JK Ghosh, M Delampady, T Samanta - 2007 - books.google.com
This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory,
methods, and applications. Starting from basic statistics, undergraduate calculus and linear …
methods, and applications. Starting from basic statistics, undergraduate calculus and linear …
Robust Bayesian analysis: sensitivity to the prior
JO Berger - Journal of statistical planning and inference, 1990 - Elsevier
It is a great pleasure to write a review paper on robust Bayesian analysis for the occasion of
IJ Good's 70th birthday conference. Good was the first Bayesian to clearly make uncertainty …
IJ Good's 70th birthday conference. Good was the first Bayesian to clearly make uncertainty …
Bayes' theorem for Choquet capacities
LA Wasserman, JB Kadane - The Annals of Statistics, 1990 - JSTOR
We give an upper bound for the posterior probability of a measurable set A when the prior
lies in a class of probability measures P. The bound is a rational function of two Choquet …
lies in a class of probability measures P. The bound is a rational function of two Choquet …
Sensitivity in Bayesian statistics: the prior and the likelihood
M Lavine - Journal of the American Statistical Association, 1991 - Taylor & Francis
One paradigm for sensitivity analyses in Bayesian statistics is to specify Γ, a reasonable
class of priors, and to compute the corresponding class of posterior inferences. The class Γ …
class of priors, and to compute the corresponding class of posterior inferences. The class Γ …
Robust bayesian analysis
We provide an overview of robust Bayesian analysis with emphasis on foundational,
decision oriented and computational approaches. Common types of robustness analyses …
decision oriented and computational approaches. Common types of robustness analyses …
Robust Bayesian credible intervals and prior ignorance
LR Pericchi, P Walley - International Statistical Review/Revue Internationale …, 1991 - JSTOR
In this paper we propose, survey and compare some classes of probability densities that
may be used to represent partial prior information, to model either prior ignorance or …
may be used to represent partial prior information, to model either prior ignorance or …
Robust Bayesian sample size determination in clinical trials
This article deals with determination of a sample size that guarantees the success of a trial.
We follow a Bayesian approach and we say an experiment is successful if it yields a large …
We follow a Bayesian approach and we say an experiment is successful if it yields a large …