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http://dx.doi.org/10.29220/CSAM.2019.26.2.191

Goodness-of-fit tests based on generalized Lorenz curve for progressively Type II censored data from a location-scale distributions  

Lee, Wonhee (Department of Statistics, Daegu University)
Lee, Kyeongjun (Division of Mathematics and Big Data Science, Daegu University)
Publication Information
Communications for Statistical Applications and Methods / v.26, no.2, 2019 , pp. 191-203 More about this Journal
Abstract
The problem of examining how well an assumed distribution fits the data of a sample is of significant and must be examined prior to any inferential process. The observed failure time data of items are often not wholly available in reliability and life-testing studies. Lowering the expense and period associated with tests is important in statistical tests with censored data. Goodness-of-fit tests for perfect data can no longer be used when the observed failure time data are progressive Type II censored (PC) data. Therefore, we propose goodness-of-fit test statistics and a graphical method based on generalized Lorenz curve for PC data from a location-scale distribution. The power of the proposed tests is then assessed through Monte Carlo simulations. Finally, we analyzed two real data set for illustrative purposes.
Keywords
generalized Lorenz curve; goodness-of-fit test; location-scale distribution; Monte Carlo simulation; power; progressive Type II censoring;
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