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The Multivariate Inclusion-Exclusion Formula and Order Statistics from Dependent Variates

多元容斥公式与相依随机变量的次序统计量

A variant of the general multivariate inclusion-exclusion formula of Meyer (1969) is derived for the case where $K$ classes of events are considered and specific subsets of the events, one from each class, are related to one another by set inclusion. This result, in turn, yields a formula for the cumulative distribution function of any subset of order statistics from dependent random variables in terms of cumulative distribution functions of subsets of the unordered…

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Tests of the Kolmogorov-Smirnov Type for Exponential Data with Unknown Scale, and Related Problems

尺度未知的指数数据的 Kolmogorov–Smirnov 型检验及相关问题

Let D^ , D^+ and D^− denote Kolmogorov-Smirnov typo one-sample statistics to test good ness of fit in the presence of unknown nuisance parameters; then the distributions of D^ , D^+ and D^− depend on the population sampled and the estimator used. Simulation has been the primary tool for studying these statistics. Recently, Durbin obtained the distributions of D^ , D^+ and D^− in terms of a Fourier transform for a wide class of underlying populations, and produced explicit…

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Tests of the Kolmogorov-Smirnov type for exponential data with unknown scale, and related problems

未知尺度指数分布的 Kolmogorov–Smirnov 型检验及相关问题

SUMMARY: Let D, D⁺ and D⁻ denote Kolmogorov-Smirnov typo one-sample statistics to test good ness of fit in the presence of unknown nuisance parameters; then the distributions of D, D⁺ and D⁻ depend on the population sampled and the estimator used. Simulation has been the primary tool for studying these statistics. Recently, Durbin obtained the distributions of D, D⁺ and D⁻ in terms of a Fourier transform for a wide class of underlying populations, and produced explicit…

AI 解读阅读原文 ↗BibTeX ↓