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AdvisorBakleezi, Ayman
AuthorAhmed, Samah Ibrahim
Available date2021-02-21T06:06:56Z
Publication Date2021-01
URIhttp://hdl.handle.net/10576/17738
AbstractThe main aim of this thesis is to investigate the problem of the goodness of fit test for Log-Logistic distribution based on empirical distribution function under Type I censored data. The maximum likelihood estimation method is used to estimate the unknown parameters of Log-Logistic distribution. A Monte Carol power studies are conducted to evaluate and compare the performance of the proposed method which is an extension to the test procedure by Pakyari and Balakrishnan (2017) with the existing classical method for several alternative distributions. The proposed method exhibits higher power compared to classical method. Additionally, applications on Type I censored real datasets for the proposed and classical methods are considered for illustrative purposes. As result from the real data it was found that the Log-Logistic model has good fit for the data
Languageen
SubjectFit Testing
Log-Logistic
Type I
Censored Data
TitleGoodness of Fit Testing for the Log-Logistic distribution Based on Type I Censored Data
TypeMaster Thesis
DepartmentApplied Statistics
dc.accessType Open Access


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