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JSRI 2020, 16(2): 507-533 Back to browse issues page
Goodness of Fit Tests based on Information Criterion for Randomly Censored Data
Fatemeh Omidi‎, Arezou Habibirad *1, Vahid Fakoor‎
1- , ahabibi@um.ac.ir
Abstract:   (576 Views)

‎We propose two goodness of fit test statistics based on‎ Cumulative Kullback--Leibler (CKL) information and Cumulative residual Kullback--Leibler (CRKL) information for exponential distributions with unknown parameter and randomly censored data‎. ‎Koziol and Green introduced the Cramér-von Mises statistic with randomly censored data for a simple hypothesis based on the Kaplan--Meier product limit of the distribution function‎. ‎We use their idea to obtain test statistics based on CKL and CRKL for a randomly censored exponential distribution with estimated parameters‎.
‎The power of the proposed tests for testing exponentiality is compared with the test statistic based on the empirical distribution function using the opinion of Koziol and Green‎. ‎A simulation study is performed under a special censorship model introduced by Koziol and Green‎. ‎Simulation studies show a relatively high power of proposed test statistics in many alternatives‎.
 
 
Keywords: Cramér-von Mises statistic, cumulative Kullback--Leibler information, cumulative residual Kullback--Leibler information, exponential distribution, Kaplan--Meier estimator, randomly censored data.
Full-Text [PDF 1977 kb]   (234 Downloads)    
Type of Study: Research | Subject: General
Received: 2021/06/19 | Accepted: 2021/09/21 | Published: 2020/03/29
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Omidi‎ F, Habibirad A, Fakoor‎ V. Goodness of Fit Tests based on Information Criterion for Randomly Censored Data. JSRI. 2020; 16 (2) :507-533
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