Using Bayesian approach to study robustness of classes of priors for homogeneous and non homogeneous Poison processes

Fatiha Talbi
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Fatiha Talbi: University of Algiers 3 (Algeria)

IJEP, 2021, vol. 4, issue 2

Abstract: A Non-Homogeneous process is a process with rate parameter (t) such that this rate is a function of time. Bayesians are interested in robustness with respect to changes in prior distributions/sampling models/loss functions. In This work, we focused on replacing a single prior distribution by a class of priors of the parameters of a given Poisson processes, and developing methods of computing the range of the ensuing answers as the prior varied over the class. This approach, called “global robustness”.

Keywords: Bayesian Robustness; Nonhomogeneous Poisson processes; Prior Robustness; Global Sensitivity; Local Sensitivity (search for similar items in EconPapers)
Date: 2021
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