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

역가우스분포에 대한 변형된 엔트로피 기반 적합도 검정

Choi, Byung-Jin

  • Received : 20110200
  • Accepted : 20110300
  • Published : 2011.04.30


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


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