The Bayesian design of Kaplan Meier estimation using Gibbs sampling : application in econometrics of duration models

Abstract EN

A Bayesian approach to survival offers practical, simple and relatively easy solutions to exploit digitally.

In this contribution, we will demonstrate the effectiveness of the Bayesian approach in the modeling of durations and in an econometric context, we propose the Bayesian design of the Kaplan Meier estimator based on the stochastic approximation, which is represented here by the Gibbs sampling.

Our contribution is to improve the deductive stage in estimating nonparametric survival times and under censorship, and this is what we reached in our research by means of the hierarchical prior distribution.