文章基本信息

标题：The Odd Lindley Burr XII Model: Bayesian Analysis, Classical Inference and Characterizations
本地全文：下载
作者：Mustafa C¸ a˘gatay Korkmaz ; Haitham M. Yousof ; Mahdi Rasekhi 等
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2018
卷号：16
期号：2
页码：327-354
出版社：Tingmao Publish Company
摘要：In this work, we study the odd Lindley Burr XII model initially introduced by Silva et al. [29]. This model has the advantage of being capable of modeling various shapes of aging and failure criteria. Some of its statistical structural properties including ordinary and incomplete moments, quantile and generating function and order statistics are derived. The odd Lindley Burr XII density can be expressed as a simple linear mixture of BurrXII densities. Useful characterizations are presented. The maximum likelihood method is used to estimate the model parameters. Simulation results to assess the performance of the maximum likelihood estimators are discussed. We prove empirically the importance and flexibility of the new model in modeling various types of data. Bayesian estimation is performed by obtaining the posterior marginal distributions as well as using the simulation method of Markov Chain Monte Carlo (MCMC) by the Metropolis-Hastings algorithm in each step of Gibbs algorithm. The trace plots and estimated conditional posterior distributions are also presented.
关键词：Burr XII model; Bayesian estimation; Metropolis–Hastings Algorithm; Multi- censored data; Markov Chain Monte Carlo; Simulation study; Gibbs Algorithm.