Symbolic computation for approximating distributions of some families of one and two-sample nonparametric test statistics

被引：4

作者：

Gatto, R ^{[1
]}

机构：

[1] Univ Bern, Inst Math Stat & Versicherungslehre, CH-3012 Bern, Switzerland

来源：

STATISTICS AND COMPUTING | 2001年 / 11卷 / 01期

关键词：

saddlepoint approximation; quantile approximation; discrete distribution; computer algebra; exponential score; likelihood ratio and Wald-Wolfowitz test statistics; goodness-of-fit tests; composite hypothesis; geometric; multinomial and Poisson distributions;

D O I：

10.1023/A:1026518218069

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A conditional saddlepoint approximation was provided by Gatto and Jammalamadaka (1999) for computing the distribution function of many test statistics based on dependent quantities like multinomial frequencies, spacing frequencies, etc. The considerable complexity of the formulas involved can be bypassed by symbolic computation. This article illustrates the effectiveness of symbolic computation to evaluate the saddlepoint approximation for the likelihood ratio, the exponential score, and the Wald-Wolfowitz test statistics. The case of composite hypotheses is also discussed.

引用

页码：89 / 95

页数：7

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