We extend Doob's well-known result on Bayesian consistency. The extension covers the case where the nonparametric prior is fully supported by densities. However, our use of martingales differs from that of Doob. We also consider rates
A Dirichlet mixture of normal densities is a useful choice for a prior distribution on densities in ...
International audienceAbstract In this paper we discuss consistency of the posterior distribution in...
In this paper, we provide a Doob-style consistency theorem for stationary models. Many applications ...
We extend Doob’s well-known result on Bayesian consistency. The extension covers the case where the ...
We extend Doob's well-known result on Bayesian consistency. The extension covers the case where the ...
We extend Doob's well-known result on Bayesian consistency The extension covers the case where the n...
We use martingales to study Bayesian consistency. We derive sufficient conditions for both Hettinger...
Asymptotics plays a crucial role in statistics. The theory of asymptotic consistency of Bayesian non...
Asymptotics plays a crucial role in statistics. The theory of asymptotic consistency of Bayesian non...
Bayesian consistency is an important issue in the context of non- parametric problems. The posterior...
We consider sufficient conditions for Bayesian consistency of the transition density of time homogen...
We consider sufficient conditions for Bayesian consistency of the transition density of time homogen...
We consider sufficient conditions for Bayesian consistency of the transition density of time homogen...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
This paper contributes to the theory of Bayesian consistency for a sequence of posterior and predict...
A Dirichlet mixture of normal densities is a useful choice for a prior distribution on densities in ...
International audienceAbstract In this paper we discuss consistency of the posterior distribution in...
In this paper, we provide a Doob-style consistency theorem for stationary models. Many applications ...
We extend Doob’s well-known result on Bayesian consistency. The extension covers the case where the ...
We extend Doob's well-known result on Bayesian consistency. The extension covers the case where the ...
We extend Doob's well-known result on Bayesian consistency The extension covers the case where the n...
We use martingales to study Bayesian consistency. We derive sufficient conditions for both Hettinger...
Asymptotics plays a crucial role in statistics. The theory of asymptotic consistency of Bayesian non...
Asymptotics plays a crucial role in statistics. The theory of asymptotic consistency of Bayesian non...
Bayesian consistency is an important issue in the context of non- parametric problems. The posterior...
We consider sufficient conditions for Bayesian consistency of the transition density of time homogen...
We consider sufficient conditions for Bayesian consistency of the transition density of time homogen...
We consider sufficient conditions for Bayesian consistency of the transition density of time homogen...
This paper introduces a new approach to the study of rates of convergence for posterior distribution...
This paper contributes to the theory of Bayesian consistency for a sequence of posterior and predict...
A Dirichlet mixture of normal densities is a useful choice for a prior distribution on densities in ...
International audienceAbstract In this paper we discuss consistency of the posterior distribution in...
In this paper, we provide a Doob-style consistency theorem for stationary models. Many applications ...
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