Empirical Likelihood Ratio Based Goodness-of-Fit Test for Generalized Lambda Distribution

被引：0

作者：

Ning, Wei ^{[1
]}

机构：

[1] Bowling Green State Univ, Dept Math & Stat, Bowling Green, OH 43403 USA

来源：

EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS | 2014年 / 7卷 / 01期

关键词：

Generalized lambda distribution; Empirical likelihood; Nonparametric; Goodness-of-fit test;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper, we propose a goodness-of-fit test based on the empirical likelihood method for the generalized lambda distribution (GLD) family. Such a nonparametric test approximates the optimal Neyman-Pearson likelihood ratio test under the unknown alternative distribution scenario. The p-value of the test is approximated through the simulations due to the dependency of the test statistic on the data. The test is applied to the roller data set and the pollen data set to illustrate the testing procedure for the sufficiency of the GLD fittings.

引用

页码：22 / 36

页数：15

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