An Alternative Estimator with Appropriate Plotting Position Estimates for the Generalized Exponential Distribution

Authors

  • Theerapong Kaewprasert Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
  • Manad Khamkong Data Science Research Center, Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand

Keywords:

Modified percentile method, maximum likelihood estimation, rainfall data, root mean square error, simulation

Abstract

In this paper, we propose an alternative method for estimating generalized exponential distributions by applying plotting positions of modified percentile estimates. We compared its efficiency with the classical maximum likelihood estimator and percentile estimator in terms of root mean square errors. Simulation results show that the percentile estimator outperformed the others for small sample sizes while the proposed estimator was most effective for medium to large sample sizes. This finding was supported by applying the proposed estimator to deduce whether Thai rainy season rainfall data followed a generalized exponential distribution from a rain gauging station in Fang district, Chiang Mai Province, Thailand.

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Published

2020-06-30

How to Cite

Kaewprasert, T., & Khamkong, M. . (2020). An Alternative Estimator with Appropriate Plotting Position Estimates for the Generalized Exponential Distribution. Thailand Statistician, 18(3), 333–339. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/241284

Issue

Vol. 18 No. 3 (2020): July

Section

Articles