New Modified Anderson Darling Goodness of Fit Test for Lognormal and Gamma distributions

Authors

  • Jutaporn Neamvonk Department of Mathematics, Faculty of Science, Burapha University, Chonburi, Thailand
  • Bumrungsak Phuenaree Department of Mathematics, Faculty of Science, Burapha University, Chonburi, Thailand

DOI:

https://doi.org/10.24203/ajas.v10i6.7124

Keywords:

Goodness of fit test, Anderson-Darling test, Kolmogorov Smirnov test, Modified Anderson-Darling test

Abstract

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.

References

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Published

2023-01-02

How to Cite

Neamvonk, J., & Phuenaree, B. (2023). New Modified Anderson Darling Goodness of Fit Test for Lognormal and Gamma distributions. Asian Journal of Applied Sciences, 10(6). https://doi.org/10.24203/ajas.v10i6.7124

Issue

Vol. 10 No. 6 (2022): December 2022

Section

Articles

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Copyright (c) 2023 Jutaporn Neamvonk, Bumrungsak Phuenaree

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