A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution

- Journal title : Korean Journal of Applied Statistics
- Volume 24, Issue 2, 2011, pp.383-391
- Publisher : The Korean Statistical Society
- DOI : 10.5351/KJAS.2011.24.2.383

Title & Authors

A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution

Choi, Byung-Jin;

Choi, Byung-Jin;

Abstract

This paper presents a modified entropy-based test of fit for the inverse Gaussian distribution. The test is based on the entropy difference of the unknown data-generating distribution and the inverse Gaussian distribution. The entropy difference estimator used as the test statistic is obtained by employing Vasicek's sample entropy as an entropy estimator for the data-generating distribution and the uniformly minimum variance unbiased estimator as an entropy estimator for the inverse Gaussian distribution. The critical values of the test statistic empirically determined are provided in a tabular form. Monte Carlo simulations are performed to compare the proposed test with the previous entropy-based test in terms of power.

Keywords

Inverse Gaussian distribution;entropy;entropy characterization;entropy estimator;entropy-based test;power;

Language

Korean

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