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A0714
Title: A new test statistic to assess the goodness of fit of exponential distribution under multiply progressive censoring Authors:  Kyeongjun Lee - Daegu University (Korea, South) [presenting]
Subin Cho - Daegu University (Korea, South)
YeongEun Hwang - Daegu University (Korea, South)
Seonghee Park - Daegu University (Korea, South)
Abstract: The exponential distribution is the probability distribution that describes the time between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate. The goodness of fit test for the exponential distribution is very important in lifetime data analysis. Therefore, we propose the two test statistics to test goodness of fit for the exponential distribution under multiply progressive type II censoring scheme. Also, we propose a new graphic method for the goodness-of-fit test for the exponential distribution under multiply progressive type II censoring scheme. We assess the new test statistic in terms of the power of the test through by Monte Carlo method. And we check the new plot and test statistic by using real data.