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

Authors

  • Wei Ning Bowling Green State University

Keywords:

Generalized lambda distribution, Empirical likelihood, Nonparametric, Goodness-of-fit test.

Abstract

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.

Author Biography

Wei Ning, Bowling Green State University

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How to Cite

Ning, W. (2014). Empirical Likelihood Ratio Based Goodness-of-Fit Test for Generalized Lambda Distribution. European Journal of Pure and Applied Mathematics, 7(1), 22–36. Retrieved from https://ejpam.com/index.php/ejpam/article/view/1842