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Goodness of fit tests for progressively type II censored data from a gumbel distribution
Journal of the Korean Data & Information Science Society 2018;29:59-69
Published online January 31, 2018
© 2018 Korean Data and Information Science Society.

Nanhee Yun1 · Kyeongjun Lee2

12Department of Computer Science and Statistics, Daegu University
Correspondence to: Assistant professor, Department of Statistics and Computer Science, Daegu University, Gyeongbuk 68453, Korea. E-mail: indra
Received December 13, 2017; Revised January 5, 2018; Accepted January 8, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The Gumbel distribution (type I generalized extreme value distribution) is used to model the distribution of the maximum of a number of samples. This distribution might be used to represent the distribution of the maximum level of a river in a particular year if there was a list of maximum values for the past ten years. The goodness of fit test for Gumbel distribution is very important in natural disaster data analysis. Therefore, we propose the two test statistics to test goodness of fit for the Gumbel distribution under progressive type II censoring. Also, we propose new graphic method to goodness of fit test for the Gumbel distribution under progressive type II censoring. We compare the new test statistic with the Pakyari and Balakrishnan (2013) test in terms of the power of the test through by Monte Carlo method. The new test statistics are more powerful than Pakyari and Balakrishnan (2013) test.
Keywords : Goodness of fit test, gumbel distribution, Lorenz curve, progressive type II censoring.