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Extended Half-Logistic Distribution with Theory and Lifetime Data Application

Author(s)
Emrah Altun Department of Statistics, Hacettepe University, Turkey.
Muhammad Nauman Khan Department of Mathematics, Kohat University of Science & Technology, Kohat, Pakistan
Morad Alizadeh Department of Statistics, Persian Gulf university, Bushehr, Iran
Gamze Ozel Department of Statistics, Hacettepe University, Turkey
Nadeem Shafique Butt Department of Family and Community Medicine, King Abdulaziz University Kingdom of Saudi Arabia
Abstract
In this paper, we introduce a new three-parameter lifetime model called the extended half-logistic (EHL) distribution. We derive various of its structural properties including moments, quantile and generating functions, mixture representation for probability density function, and reliability curves. The maximum likelihood, ordinary and weighted least square methods are used to estimate the model parameters. Simulation results to assess the performance of the estimation methods are discussed. We conclude that the maximum likelihood is the most suitable method to estimate model parameters for the small sample size. While the weighted least square method is the best for the large sample size. Finally, we prove empirically the importance and flexibility of the new model in modeling a real lifetime dataset.
Publication Details
Page(s) 319-331
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 14, Issue: 2, Year: 2018

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Keywords
Meijer's -functions, Half-logistic distribution, Weighted Least Square
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