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A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution
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 Title & Authors
A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution
Choi, Byung-Jin;
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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.
Inverse Gaussian distribution;entropy;entropy characterization;entropy estimator;entropy-based test;power;
 Cited by
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