RT - Journal Article T1 - Hyperbolic Cosine Log-Logistic Distribution and Estimation of Its Parameters by Using Maximum Likelihood Bayesian and Bootstrap Methods JF - Andishe-_ye-Amari YR - 2018 JO - Andishe-_ye-Amari VO - 22 IS - 2 UR - http://andisheyeamari.irstat.ir/article-1-495-en.html SP - 111 EP - 123 K1 - ‎Hyperbolic cosine function‎ K1 - ‎Log-Logistics distribution‎ K1 - ‎Mean residual lifetime‎ K1 - ‎Maximum likelihood estimation‎ K1 - ‎Bootstrap‎. AB - ‎In this paper‎, ‎a new probability distribution‎, ‎based on the family of hyperbolic cosine distributions is proposed and its various statistical and reliability characteristics are investigated‎. ‎The new category of HCF distributions is obtained by combining a baseline F distribution with the hyperbolic cosine function‎. ‎Based on the base log-logistics distribution‎, ‎we introduce a new distribution so-called HCLL and derive the various properties of the proposed distribution including the moments‎, ‎quantiles‎, ‎moment generating function‎, ‎failure rate function‎, ‎mean residual lifetime‎, ‎order statistics and stress-strength parameter‎. ‎Estimation of the parameters of HCLL for a real data set is investigated by using three methods‎: ‎maximum likelihood‎, ‎Bayesian and bootstrap (parametric and non-parametric)‎. ‎We evaluate the efficiency of the maximum likelihood estimation method by Monte Carlo simulation‎. ‎In addition‎, ‎in the application section‎, ‎by using a realistic data set‎, ‎the superiority of HCLL model to generalized exponential‎, ‎Weibull‎, ‎hyperbolic cosine exponential‎, ‎gamma‎, ‎weighted exponential distributions is shown through the different criteria of selection model‎. LA eng UL http://andisheyeamari.irstat.ir/article-1-495-en.html M3 ER -