Statistical inference for the geometric distribution based on δ-records

New inferential procedures for the geometric distribution, based on δ-records, are developed. Maximum likelihood and Bayesian approaches for parameter estimation and prediction of future records are considered. The performance of the estimators is compared with those based solely on record-breaking data by means of Monte Carlo simulations, concluding that the use of δ-records is clearly advantageous. An example using real data is also discussed.

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Year of publication:	2014
Authors:	Gouet, Raúl ; López, F. Javier ; Maldonado, Lina P. ; Sanz, Gerardo
Published in:	Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 78.2014, C, p. 21-32
Publisher:	Elsevier
Subject:	δ-records \| Geometric distribution \| Maximum likelihood estimation \| Bayes estimation \| Empirical Bayes \| Maximum likelihood prediction \| Bayes prediction

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011056413