Afrika Statistika

Empirical Estimation Based On Progressive First Failure Censored Generalized Pareto Data

Gyan Prakash

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The Progressive First-Failure (PFF) censoring scheme is considered in the present article for the Empirical Bayes estimation. The approximate confidence intervals and the Bayes estimation for the unknown parameters under the empirical Bayesian technique are obtained for the Generalized Pareto distribution. The improved approximate confidence intervals are discussed also. A simulation technique is applied here for illustrating the methods based on different censoring plans, those are the special cases of PFF censoring scheme.


Le schéma de censure du premier échec progressif (PFF) est considéré dans le présent article pour l'estimation empirique de Bayes. Les intervalles de confiance approximatifs et l'estimation de Bayes pour les paramètres inconnus sous la méthode bayésienne empirique sont obtenus pour la distribution de Pareto généralisée. Les intervalles de confiance approximatifs améliorés sont également discutés. Une technique de simulation est appliquée ici pour illustrer les méthodes basées sur différents plans de censure, qui sont les cas particuliers du schéma de censure PFF.

Article information

Afr. Stat., Volume 13, Number 2 (2018), 1683-1697.

First available in Project Euclid: 7 June 2018

Permanent link to this document

Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62A15 62F15: Bayesian inference 65C05: Monte Carlo methods

Generalized Pareto Distribution Empirical Bayes Estimation Progressive First-Failure (PFF) Censoring Approximate Confidence Intervals (ACI)


Prakash, Gyan. Empirical Estimation Based On Progressive First Failure Censored Generalized Pareto Data. Afr. Stat. 13 (2018), no. 2, 1683--1697. doi:10.16929/as/1683.128.

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