Abstract
Truncated type I generalized logistic distribution has been used in a variety of applications. In this article, a new bivariate truncated type I generalized logistic (BTTGL) distributional models driven from three different copula functions are introduced. A study of some properties is illustrated. Parametric and semiparametric methods are used to estimate the parameters of the BTTGL models. Maximum likelihood and inference function for margin estimates of the BTTGL parameters are compared with semiparametric estimates using real data set. Further, a comparison between BTTGL, bivariate generalized exponential and bivariate exponentiated Weibull models is conducted using Akaike information criterion and the maximized log-likelihood. Extensive Monte Carlo simulation study is carried out for different values of the parameters and different sample sizes to compare the performance of parametric and semiparametric estimators based on relative mean square error.
Highlights
Truncated logistic distribution has been used effectively in different lifetime applications
A new bivariate truncated type I generalized logistic (BTTGL) distributional models driven from three different copula functions are introduced
The proposed bivariate distributional models derived from commonly used copula functions with truncated generalized logistic distribution as marginals
Summary
Truncated logistic distribution has been used effectively in different lifetime applications. It was first introduced by Kjelsberg (1962) and Balakrishnan (1985) studied the half-logistic distribution and its use as lifetime model. Several authors considered different copula functions to construct bivariate and multivariate distributions. These include multivariate Gompertz-Type distribution (Adham & Walker, 2001), bivariate half- logistic-type distribution (Adham et al 2009), bivariate Birnbaum-Saunders distribution derived from Gaussian copula (Kundu, Balakrishnan, & Jamalizadeh, 2010), bivariate http://ijsp.ccsenet.org
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