SOME PARAMETRIC, NONPARAMETRIC AND PERMUTATION INFERENCE PROCEDURES RESULTING FROM WEATHER-MODIFICATION EXPERIMENTS

被引：9

作者：

MIELKE, PW

机构：

[1] Department of Statistics, Colorado State University, Fort Collins

来源：

COMMUNICATIONS IN STATISTICS PART A-THEORY AND METHODS | 1979年 / 8卷 / 11期

关键词：

classes of nonpa rametric tests; multivariate inference tech-niques new sample unvariate nonparametric tests; univariate and bivariate parametric models;

D O I：

10.1080/03610927908827816

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Techniques and problems are presented which have resulted from statistical efforts concerning weather modification pro-jects. Specific topics include (i) descriptions of various univariate distributions used to approximate meteorological data, (ii) interpretations of statistical results involving transformation effects on covariance analyses, (iii) application of classes of nonparametric tests which provide indications on how treatment effects might have occurred, and (iv) recent techniques for analyzing multivariate data which are free of distributional assumptions. © 1979, Taylor & Francis Group, LLC. All rights reserved.

引用

页码：1083 / 1096

页数：14

共 41 条

[21]

MIELKE PW, UNPUBLISHED

[22]

MIELKE PW, J APPL METEOR, V15, P801

[23] STATISTICAL INFERENCE WITH BIVARIATE GAMMA DISTRIBUTIONS [J].