Abstract
In this article, we propose inverse Gaussian correlated frailty model based on logistic exponential as baseline distribution. The Bayesian approach of Markov Chain Monte Carlo (MCMC) technique was employed to estimate the parameters involved in the models. A simulation study was performed to compare the true values and estimated value of the parameters. Comparison of the proposed model with correlated gamma frailty model and without frailty model was done using Bayesian comparison techniques. The better model for the infectious disease data related to kidney infection is also suggested.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Communications in Statistics - Simulation and Computation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
