Add to ORKGWe consider the asymptotic behavior of posterior distributions and Bayes estimators for infinite-dimensional statistical models. We give general results on the rate of convergence of the posterior measure. These are applied to several examples, including priors on finite sieves, log-spline models, Dirichlet processes and interval censoring
Much is now known about the consistency of Bayesian updating on infinite-dimensional parameter space...
Rates of convergence of Bayesian nonparametric procedures are expressed as the maximum between two r...
AbstractIn this paper, the asymptotic behavior of posterior distributions on parameters contained in...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
We consider the asymptotic behavior of posterior distributions and Bayes estimators based on observa...
This dissertation focuses on the frequentist properties of Bayesian procedures in a broad spectrum o...
This dissertation focuses on the frequentist properties of Bayesian procedures in a broad spectrum o...
We consider the asymptotic behaviour of posterior distributions based on continuous observations fro...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
We consider the asymptotic behaviour of posterior distributions based on continuous observations fro...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
Much is now known about the consistency of Bayesian updating on infinite-dimensional parameter space...
Rates of convergence of Bayesian nonparametric procedures are expressed as the maximum between two r...
AbstractIn this paper, the asymptotic behavior of posterior distributions on parameters contained in...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
We consider the asymptotic behavior of posterior distributions and Bayes estimators based on observa...
This dissertation focuses on the frequentist properties of Bayesian procedures in a broad spectrum o...
This dissertation focuses on the frequentist properties of Bayesian procedures in a broad spectrum o...
We consider the asymptotic behaviour of posterior distributions based on continuous observations fro...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
We consider the asymptotic behaviour of posterior distributions based on continuous observations fro...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
We consider the problem of estimating the mean of an infinite-break dimensional normal distribution ...
Much is now known about the consistency of Bayesian updating on infinite-dimensional parameter space...
Rates of convergence of Bayesian nonparametric procedures are expressed as the maximum between two r...
AbstractIn this paper, the asymptotic behavior of posterior distributions on parameters contained in...