Goodness of Fit Testing for the Log-logistic Distribution Based on Type I Censored Data
A goodness of fit test procedure is proposed for the log-logistic distribution when the available data are subject to Type I censoring. The proposed test is based on transforming type 1 censored data into complete data from a suitably truncated distribution. A Monte Carlo power study is conducted to evaluate and compare the performance of the proposed method with the existing classical methods. An application based on a real dataset is considered for illustrative purposes
Copyright (c) 2023 Samah Ahmed, Ayman Baklizi, Reza Pakyari
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