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Testing Exponentiality Based on Kullback-Leibler Information With Progressively Type-II Censored Data

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3 Author(s)
Narayanaswamy Balakrishnan ; Dept. of Math. & Stat., McMaster Univ., Hamilton, Ont. ; Arezou Habibi Rad ; Naser Reza Arghami

We express the joint entropy of progressively censored order statistics in terms of an incomplete integral of the hazard function, and provide a simple estimate of the joint entropy of progressively Type-II censored data. We then construct a goodness-of-fit test statistic based on Kullback-Leibler information with progressively Type-II censored data. Finally, by using Monte Carlo simulations, the power of the test is estimated, and compared against several alternatives under different progressive censoring schemes

Published in:

IEEE Transactions on Reliability  (Volume:56 ,  Issue: 2 )