Confidence interval estimation of P(Y<X) in the Gamma Case

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)225-244
Journal / PublicationCommunications in Statistics - Simulation and Computation
Volume19
Issue number1
Publication statusPublished - 1990
Externally publishedYes

Abstract

This paper is concerned with the problem of interval estimation of R = P(Y<X) when X and Y are independent gamma random variables. We compare ten different confidence interval estimators. An important thrust of this paper is to employ bootstrapping methodology to address the problem of robustness with respect to the shape parameters of the gamma distributions. We believe that bootstrapping provides a powerful methodology for studying these problems. Seven of the ten confidence interval estimators considered are based on bootstrapping. Simulation results are presented and discussed, with robustness recommendations.

Research Area(s)

  • bootstrap, confidence interval, MLE, MSE

Citation Format(s)

Confidence interval estimation of P(Y<X) in the Gamma Case. / Constantine, Kenneth; Karson, Marvin J.; Tse, Siu-Keung.
In: Communications in Statistics - Simulation and Computation, Vol. 19, No. 1, 1990, p. 225-244.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review