Goodness-of-fit test for progressively censored data from Weibull distribution†
Kyeongjun Lee1 · Yeongmin Kim2 · Sangjun Lee3 · Jihoo Choi4
1Department of Mathematics and Big Data Science, Kumoh National Institute of Technology
234Daegu Science High School
234Daegu Science High School
Correspondence to: † This research was supported by Daegu Science High School Research Program, 2022.
1 Assistant professor, Department of Mathematics and Big Data Science, Kumoh National Institute of Technology, Gyeonbuk 49177, Korea. E-mail: leekj@kumoh.ac.kr
2 Student, Daegu Science High School, Daegu 42110, Korea.
3 Student, Daegu Science High School, Daegu 42110, Korea.
4 Student, Daegu Science High School, Daegu 42110, Korea.
1 Assistant professor, Department of Mathematics and Big Data Science, Kumoh National Institute of Technology, Gyeonbuk 49177, Korea. E-mail: leekj@kumoh.ac.kr
2 Student, Daegu Science High School, Daegu 42110, Korea.
3 Student, Daegu Science High School, Daegu 42110, Korea.
4 Student, Daegu Science High School, Daegu 42110, Korea.
Received October 30, 2022; Revised November 8, 2022; Accepted November 11, 2022.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Abstract
- There are many areas of applications where Weibull distribution are employed such as reliability engineering and electrical engineering. The goodness-of-fit test forWeibull distribution is very important in survaival and failure data analysis. In most of the life testing experiments, the experimenter is often, unable to observe life time of all items put on test and the data available to the experimenter is progressive censored data. Therefore, we propose the test statistics to test goodness of fit for the Weibull distribution under progressive censoring scheme using income inequality index - Lorenz curve and decile dispersion ratio. We compare the new test statistic in terms of the power of the test through by Monte Carlo simulation method. As a result, the new test statistic using decile dispersion ratio are more powerful than test statistic using Lorenz curve. Also, we check the proposed test statistics using example data.
- Keywords : Decile dispersion ratio, goodness-of-fit test, Lorenz curve, progressive censoring scheme, Weibull distribution.
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