高维伯恩斯坦-冯·米塞斯:简单的例子。

Iain M Johnstone
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引用次数: 0

摘要

在具有高斯先验的高斯序列模型中,我们开发了一些简单的例子来说明当维数p随样本量n增加时后验概率和频率概率匹配的三种观点:(i)联合后验分布的收敛性,(ii)非线性泛函的行为:平方误差损失,以及(iii)线性泛函的估计。就伯恩斯坦-冯·米塞斯定理的有效性所需要的条件而言,这三种情况的要求越来越低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

High dimensional Bernstein-von Mises: simple examples.

High dimensional Bernstein-von Mises: simple examples.

In Gaussian sequence models with Gaussian priors, we develop some simple examples to illustrate three perspectives on matching of posterior and frequentist probabilities when the dimension p increases with sample size n: (i) convergence of joint posterior distributions, (ii) behavior of a non-linear functional: squared error loss, and (iii) estimation of linear functionals. The three settings are progressively less demanding in terms of conditions needed for validity of the Bernstein-von Mises theorem.

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