A new bivariate survival model: modeling, inference and influence analysis

• Grant number: 21/01977-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2021
• End date: April 30, 2022
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Statistics
• Principal Investigator: Adriano Kamimura Suzuki
• Grantee: Natan Hilario da Silva
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

In this work we propose a new bivariate survival model based on Farlie-Gumbel-Morgenstern (FGM) copula with marginals following A distribution to model complete data or in the presence of censored observations. For inferential purposes, we carry out a Bayesian approach using Markov chain Monte Carlo (MCMC) methods. In order to detect possible influential we will use the Bayesian method of influence analysis of case deletion based psi-divergence. We will show its applicability to simulated and real data sets. All computational implementations will be performed using the JAGS and R systems. (AU)