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Additive Shared Inverse Gaussian Frailty Model.

Author(s)
Arvind Pandey Department of Statistics, Central University of Rajasthan, India
Shashi Bhushan Department of Mathematics and Statistics, Dr. Shakuntala Misra National Rehabilitation University, Lucknow, Uttar Pradesh, India
Lalpawimawha Pachhunga University College, Aizawl, Mizoram, India
Abstract
The study proposes additive hazard shared inverse Gaussian frailty model with generalized Pareto, generalized Rayleigh and xgamma distributions as baseline distribution to analyze the bivariate data set of McGilchrist and Aisbett (1991). The estimation of the parameters involved in the models was done by Bayesian approach of Markov Chain Monte Carlo technique. The true values and the estimated values of the parameters are compared by using simulation study. The proposed models are fitted to the real life data set and the best model suggested for the data.
Publication Details
Page(s) 311-330
DOI DOI not available
Published Journal: Pakistan Journal of Statistics, Volume: 34, Issue: 4, Year: 2018

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Keywords
xgamma distribution., inverse Gaussian frailty, generalized Rayleigh distribution, generalized Pareto distribution
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