A new four-parameter extension of Burr-XII distribution: its properties and applications

被引：0
|
作者：
Laba Handique
Subrata Chakraborty
机构：
[1] Dibrugarh University,Department of Statistics
来源：
Japanese Journal of Statistics and Data Science | 2018年 / 1卷 / 2期
关键词：
Generalized Marshall–Olkin family; AIC; BIC; Anderson–Darling; Cram′er–von Mises; Likelihood ratio test;
D O I：
10.1007/s42081-018-0016-4
中图分类号：
学科分类号：
摘要：
A new four-parameter flexible extension of the Burr-XII distribution is proposed. A genesis for this distribution is presented. Some well-known distributions are shown as special and related cases. Linear expansions for survival and density functions, moment-generating function, ordinary moments, incomplete moments, quantile function, stochastic orderings and stress–strength reliability are investigated. The proposed distribution is compared with its submodels and some existing generalizations of Burr-XII for modeling five real-life data sets estimating parameters by maximum likelihood method. In all the examples, the proposed model is found to be the best one in terms of different goodness-of-fit tests as well as model selection criteria.
引用
收藏
页码：271 / 296
页数：25
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