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Integration of prior information in Kaplan Meier estimator using Bayesian approach
ISSN: 2716 - 9375
Publisher: author
Integration of prior information in Kaplan Meier estimator using Bayesian approach
Indexed in
Biology and Life Sciences
ARTICLE-FACTOR
1.3
Article Basics Score: 2
Article Transparency Score: 2
Article Operation Score: 3
Article Articles Score: 2
Article Accessibility Score: 2
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-0402
Publisher: Algerian Journal Of Biosciences
International Journal Address (IAA):
IAA.ZONE/2716118799375
eISSN
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2716 - 9375
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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.
