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比较多个正态均值与指定标准的两种选择程序AI 解读

The problem of comparing k normal means with a specified (absolute) standard is considered. A single-stage and a two-stage (k + 1)-decision procedure are proposed for the cases of common known variance and common unknown variance, respectively. The procedures guarantee that (1) with probability at least P 0* (specified), no population is selected when the largest population mean is sufficiently less than the standard, and (2) with probability at least P 1* (specified), the…

具有块协方差结构的多元正态积分的迭代积分表示AI 解读

It is shown that a km-variate normal probability integral over a rectangular region can be expressed as an iterated k-variate normal integral when the k sets of m variates each have a certain commonly realized block covariance structure. The latter representation is much easier to evaluate numerically than is the former. This result generalizes previous results for k= 1 of Dunnett & Sobel and Steck & Owen.

块协方差结构下多元正态积分的迭代积分表示AI 解读

It is shown that a km-variate normal probability integral over a rectangular region can be expressed as an iterated k-variate normal integral when the k sets of m variates each have a certain commonly realized block covariance structure. The latter representation is much easier to evaluate numerically than is the former. This result generalizes previous results for k= 1 of Dunnett & Sobel and Steck & Owen.

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共同方差未知时正态总体均值排序的两次抽样多重决策程序AI 解读

A multiple decision approach to the problem of ranking populations according to their population means has been formulated by Bechhofer (1954). A single-sample solution to this problem was presented by him for the case of normal populations with known variances. In the present paper the case of normal populations with unknown equal variances is considered. A two-sample procedure is proposed as a solution to the latter problem; this procedure is of the type used by Stein…