Modeling Statistic Distributions for Nonparametric Goodness-of-Fit Criteria for Testing Complex Hypotheses with Respect to the Inverse Gaussian Law

被引：6

作者：

Lemeshko, B. Yu. ^{[1
]}

Lemeshko, S. B. ^{[1
]}

Nikulin, M. S. ^{[2
]}

Saaidia, N. ^{[2
]}

机构：

[1] Novosibirsk State Tech Univ, Novosibirsk, Russia

[2] Victor Segalen Univ Bordeaux 2, Bordeaux, France

来源：

AUTOMATION AND REMOTE CONTROL | 2010年 / 71卷 / 07期

基金：

俄罗斯基础研究基金会;

关键词：

KOLMOGOROV-SMIRNOV TEST; PARAMETERS; NORMALITY; MISES;

D O I：

10.1134/S000511791007009X

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We give percentage point tables and statistic distribution models for non-parametric goodness-of-fit criteria for testing complex hypothesis with respect to the inverse Gaussian law in case of using maximal likelihood estimates.

引用

页码：1358 / 1373

页数：16

共 2 条

[1] Models of Statistic Distributions of Nonparametric Goodness-of-Fit Tests in Composite Hypotheses Testing for Double Exponential Law Cases
Lemeshko, B. Yu.
Lemeshko, S. B.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2011, 40 (16) : 2879 - 2892
[2] Construction of statistic Distribution Models for Nonparametric Goodness-of-Fit Tests in Testing Composite Hypotheses: The Computer Approach
Lemeshko, Boris Yu.
Lemeshko, Stanislav B.
QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT, 2011, 8 (04): : 359 - 373

← 1 →