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与给定模型相容的推断之存在性AI 解读

4 If ${p_{\theta}$ is a $\sigma$-additive statistical model and $\pi$ a finitely additive prior, then any statistic T is sufficient, with respect to a suitable inference consistent with ${p_{\theta}$ and $\pi$, provided only that $p_{\theta}(T = t) = 0$ for all $\theta$ and t. Here, sufficiency is to be intended in the Bayesian sense, and consistency in the sense of Lane and Sudderth. As a corollary, if ${p_{\theta}$ is $\sigma$-additive and diffuse, then, whatever the prior $…

相容推断与非正常先验AI 解读

Formal posteriors for improper priors are investigated in connection with coherence, both in the sense of Regazzini and of Heath and Sudderth. Those priors $\pi$ which are linked with the improper prior $\gamma$ by the relation $\pi(B) = 0$ whenever $\gamma(B) < +\infty$ are studied in particular. Moreover, a characterization of the inferences which are coherent according to Heath and Sudderth is found, and several examples, exhibiting several phenomena, are given.

相容统计推断与贝叶斯定理AI 解读

Conditions are given which suffice for the assessment of a coherent inference by means of a Bayesian algorithm, i.e., a suitable extension of the classical Bayes theorem relative to a finite number of alternatives. Under some further hypotheses such inference is shown to be, in addition, coherent in the sense of Heath, Lane and Sudderth. Moreover, a characterization of coherent posteriors is provided, together with some remarks concerning finitely additive conditional…