New Modified Anderson Darling Goodness of Fit Test for Lognormal and Gamma distributions
DOI:
https://doi.org/10.24203/ajas.v10i6.7124Keywords:
Goodness of fit test, Anderson-Darling test, Kolmogorov Smirnov test, Modified Anderson-Darling testAbstract
The purpose of this study is to present the new modified Anderson-Darling goodness of fit test, and compare to the efficiency of three tests; Kolmogorov Smirnov test, Anderson-Darling test and Zhang (2002) test. A simulation study is used to estimate the critical values at a significance level of 0.05. The type I error rate and test power are calculated using Monte Carlo simulation with 10,000 replicates. The data are generated from the specified distribution; i.e., Lognormal and Gamma distributions with sample size of 10, 20, 30, 50, 100 and 200. The results demonstrate that every test has control over the type I error probability. The new test has the highest power for two alternative hypotheses; Loglogistic and Logistic distributions. Moreover, when the alternative distribution is Normal distribution and the sample size is small, the new test has the highest power.
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Copyright (c) 2023 Jutaporn Neamvonk, Bumrungsak Phuenaree
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright © The Author(s). This article is published under the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
