De Finetti's theorem, also called the de Finetti-Hewitt-Savage theorem, is a foundational result in probability and statistics. Roughly, it says that an infinite sequence of exchangeable random variables can always be written as a mixture of independent and identically distributed (i.i.d.) sequences of random variables. In this paper, we consider a weighted generalization of exchangeability that allows for weight functions to modify the individual distributions of the random variables along the sequence, provided that -- modulo these weight functions -- there is still some common exchangeable base measure. We study conditions under which a de Finetti-type representation exists for weighted exchangeable sequences, as a mixture of distributions which satisfy a weighted form of the i.i.d. property. Our approach establishes a nested family of conditions that lead to weighted extensions of other well-known related results as well, in particular, extensions of the zero-one law and the law of large numbers.
翻译:De Finetti定理,也称为De Finetti-Hewitt-Savage定理,是概率统计学中的一个基础性结果。大致上,它指出,无限个可交换的随机变量序列可以总是被写成独立同分布(iid)序列的混合。在本文中,我们考虑了一种称为加权交换性的推广,允许权重函数修改随机变量序列中的各个分布,只要在这些权重函数的作用下,仍然存在某个共同的可交换基础测度。我们研究了一个De Finetti类型表示在加权交换序列中的存在条件,作为满足加权形式iid性质的分布混合物。我们的方法还创建了一系列嵌套的条件,以推广其他已知相关结果,特别是零-一定律和大数定律。