ENFOQUE BAYESIANO DEL MODELO DE REGRESION LOGISTICA USANDO CADENAS DE MARKOV MONTE CARLO

Abstract

The Logistic Regression is a highly used model on different areas of science where the response variable of studied problems is binary. This model can be studied under the Bayesian approach, nonetheless calculations might be complicated even using computation methods, is for that reason we use MCMC methods, which are iterative methods to obtain an approximation of the posterior distribution of model parameters. We use the R software to obtain the distribution with the MCMC method. On this work we implement the logistic regression through a simulation study under the Bayesian Approach applied to the cognitive health state on elders in the state of Guerrero