Add to ORKGThis paper is a companion paper of Florens and Mouchart [1977]. It provides some basic tools for the reducion of Bayesian experiments, in particular for the analysis of identification, sufficiency and ancillarity
A condition needed for testing nested hypotheses from a Bayesian viewpoint is that the prior for th...
. Special conditional independence structures have been recognized to be matroids. This opens new po...
. The problem of hypothesis testing is examined from both the historical and the Bayesian points of...
In this paper, the concept of invariance, standard in measure theory, is extended to the conditional...
This article introduces a Bayesian nonparametric method for quantifying the relative evidence in a d...
Abstract: As the paper explains, it is crucial to epistemology in general and to the theory of causa...
Quite frequently diagnosis is not final with one medical test but a sequence of tests are applied. Ho...
The goal of the paper is to recall a recently introduced concept of conditional independence in evid...
In this paper we propose a new procedure for testing independence of random variables, which is base...
A general definition of a conditional model is proposed through embedding that concept into the usua...
Conditional independence tests have received special attention lately in machine learning and comput...
Conditional independence tests have received special attention lately in machine learning and comput...
Conditional independence almost everywhere in the space of the conditioning variates does not imply ...
Conditional independence tests (CI tests) have received special at-tention lately in Machine Learnin...
Our aim in this paper is to clarify the notion of independence for imprecise probabilities. Suppose ...
A condition needed for testing nested hypotheses from a Bayesian viewpoint is that the prior for th...
. Special conditional independence structures have been recognized to be matroids. This opens new po...
. The problem of hypothesis testing is examined from both the historical and the Bayesian points of...
In this paper, the concept of invariance, standard in measure theory, is extended to the conditional...
This article introduces a Bayesian nonparametric method for quantifying the relative evidence in a d...
Abstract: As the paper explains, it is crucial to epistemology in general and to the theory of causa...
Quite frequently diagnosis is not final with one medical test but a sequence of tests are applied. Ho...
The goal of the paper is to recall a recently introduced concept of conditional independence in evid...
In this paper we propose a new procedure for testing independence of random variables, which is base...
A general definition of a conditional model is proposed through embedding that concept into the usua...
Conditional independence tests have received special attention lately in machine learning and comput...
Conditional independence tests have received special attention lately in machine learning and comput...
Conditional independence almost everywhere in the space of the conditioning variates does not imply ...
Conditional independence tests (CI tests) have received special at-tention lately in Machine Learnin...
Our aim in this paper is to clarify the notion of independence for imprecise probabilities. Suppose ...
A condition needed for testing nested hypotheses from a Bayesian viewpoint is that the prior for th...
. Special conditional independence structures have been recognized to be matroids. This opens new po...
. The problem of hypothesis testing is examined from both the historical and the Bayesian points of...