Integration of prior information in Kaplan Meier estimator using Bayesian approach

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AJB (20-007) Hamimes et al
Published: Dec 30, 2020
DOI: https://doi.org/10.57056/ajb.v1i2.30
Keywords:
Bayesian approach, nonparametric survival, Kaplan Meier, Bayesian estimator

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Ahmed Hamimes

Abstract

As part of this contribution, we will illustrate the effectiveness of the Bayesian approach in estimating durations; we suggest a new definition of the Kaplan Meier Bayesian estimator based on a stochastic approximation under an informative prior. For this reason, based on the lognormal distribution, we have unconjugated a priori distributions. This method of processing makes it possible to assume that the use of the a priori data with the various suggested methods is sensitive to the choices of the parameters added.

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How to Cite
Hamimes, A. (2020). Integration of prior information in Kaplan Meier estimator using Bayesian approach. Algerian Journal of Biosciences, 1(2), 076–082. https://doi.org/10.57056/ajb.v1i2.30
Issue
Vol. 1 No. 2 (2020): Alger. j. biosciences (Dec 2020)
Section
Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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