Distribución predictiva bayesiana para modelos de pruebas de vida vía MCMC

Translated title of the contribution: The bayesian predictive distribution in life testing models via MCMC

Carlos Javier Barrera, Juan Carlos Correa

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

In reliability studies it is common to not know the population parameters, therefore, it becomes necessary to collect a sample in order to estimate the parameters of the assumed probability distribution. Bayesian methods allow to incorporate subjective information about uncertainties regarding the parameter or parameters of interest. From the bayesian point of view, the uncertainty about the true value of a parameter of interest θ in the population, is modeled by the prior density function π(θ), (θ ∈ Θ). We will implement the methodology MCMC to obtain the predictive bayesian distributions, which requires the calibration, design, implementation, in addition to the validation of appropriate algorithms.

Translated title of the contributionThe bayesian predictive distribution in life testing models via MCMC
Original languageSpanish
Pages (from-to)145-155
Number of pages11
JournalRevista Colombiana de Estadistica
Volume31
Issue number2
Publication statusPublished - Dec 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

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