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Exhaustivité, ancillarité et identification en statistique bayesienne

Jean-Pierre Florens and Michel Mouchart

Annals of Economics and Statistics, 1986, issue 4, 63-93

Abstract: A Bayesian experiment is defined by a unique probability on the product of the parameter space and the sample space. This joint probability determines a conditional independance relation which is used for a symmetrical analysis of sufficiency and ancillarity on the parameter and the sample. Identification is then considered as a property of minimal sufficiency on the parameter space. These concepts are extended to conditional models and are shown to be suitable for a study of the exogeneity property in a coherent statistical framework.

Date: 1986
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