On Bivariate Nadarajah-Haghighi Distribution derived from Farlie-Gumbel-Morgenstern copula in the Presence of Covariates

Yakubu Aliyu, U. Usman
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Abstract

An important alternative distribution to the Weibull, generalized exponen-tial and gamma distributions that is used in survival analysis is the Nadarajah-Haghighi exponential distribution. Similar to the Weibull, generalized exponen-tial and gamma distributions, the Nadarajah-Haghighi exponential distributionis an extension of the well known exponential distribution. In this paper, a copulafunction commonly used to model very weak linear dependence was used to intro-duced a bivariate Nadarajah-Haghighi distribution. The joint survival function,joint probability density function and joint cumulative distribution were givenin closed form. Bayesian method of estimation was used to estimate the modelparameters considering the presence of right censoring and covariates. Posteriorsummaries of interest were obtained via standard Markov Monte Carlo (MCMC )technique. Two real data sets were used to illustrate the importance and flexi-bility of the bivariate model in comparison with some competing models. It wasobserved that, the bivariate Nadarajah-Haghighi distribution provides a better fltthan bivariate exponential, bivariate Weibull, bivariate generalized exponentialand bivariate modified Weibull distributions.
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存在协变量时由Farlie-Gumbel-Morgenstern联结导出的二元Nadarajah-Haghighi分布
在生存分析中使用的Weibull分布、广义指数分布和gamma分布的一个重要替代分布是Nadarajah-Haghighi指数分布。与Weibull、广义指数分布和gamma分布类似,Nadarajah-Haghighi指数分布是众所周知的指数分布的扩展。本文利用一个通常用于模拟极弱线性依赖的共函数,引入了二元Nadarajah-Haghighi分布。给出了联合生存函数、联合概率密度函数和联合累积分布的封闭形式。考虑右截距和协变量的存在,采用贝叶斯估计方法对模型参数进行估计。通过标准马尔可夫蒙特卡罗(MCMC)技术获得感兴趣的后验摘要。用两个真实的数据集来说明与一些竞争模型相比,二元模型的重要性和灵活性。结果表明,二元Nadarajah-Haghighi分布比二元指数分布、二元威布尔分布、二元广义指数分布和二元修正威布尔分布具有更好的平滑性。
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