A new four-parameter lifetime distribution

被引:12
|
作者
Alizadeh, Mojtaba [1 ]
Bagheri, Seyyed Fazel [2 ]
Alizadeh, Mohammad [3 ]
Nadarajah, Saralees [4 ]
机构
[1] Stat Ctr Iran, Branch Mazandaran, Sari, Iran
[2] Islamic Azad Univ, Yadegar E Imam Khomeini RAH Branch, Dept Math, Coll Basic Sci, Tehran, Iran
[3] Univ Mazandaran, Dept Math Sci, Mazandaran, Iran
[4] Univ Manchester, Sch Math, Manchester, Lancs, England
关键词
Exponentiated power Lindley distribution; maximum likelihood estimation; modelselection criteria; probability weighted moments; residual life function; EXPONENTIATED WEIBULL FAMILY; BATHTUB FAILURE-RATE; RELIABILITY PROPERTIES; LINDLEY DISTRIBUTION; POISSON DISTRIBUTION; MOMENTS;
D O I
10.1080/02664763.2016.1182137
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Generalizing lifetime distributions is always precious for applied statisticians. In this paper, we introduce a new four-parameter generalization of the exponentiated power Lindley (EPL) distribution, called the exponentiated power Lindley geometric (EPLG) distribution, obtained by compounding EPL and geometric distributions. The new distribution arises in a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the maximum lifetime value among all risks. The distribution exhibits decreasing, increasing, unimodal and bathtub-shaped hazard rate functions, depending on its parameters. It contains several lifetime distributions as particular cases: EPL, new generalized Lindley, generalized Lindley, power Lindley and Lindley geometric distributions. We derive several properties of the new distribution such as closed-form expressions for the density, cumulative distribution function, survival function, hazard rate function, the rth raw moment, and also the moments of order statistics. Moreover, we discuss maximum likelihood estimation and provide formulas for the elements of the Fisher information matrix. Simulation studies are also provided. Finally, two real data applications are given for showing the flexibility and potentiality of the new distribution.
引用
收藏
页码:767 / 797
页数:31
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