Abstract
This article considers the estimation of R = P(Y < X) when X and Y are distributed as two independent three-parameter generalized exponential (GE) random variables with different shape parameters but having the same location and scale parameters. A modified maximum likelihood method and a Bayesian technique are used to estimate R on the basis of independent complete samples. The Bayes estimator cannot be obtained in explicit form, and therefore it has been determined using an importance sampling procedure. An analysis of a real life data set is presented for illustrative purposes.
Original language | English |
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Pages (from-to) | 2854-2864 |
Number of pages | 11 |
Journal | Communications in Statistics - Theory and Methods |
Volume | 37 |
Issue number | 18 |
DOIs | |
Publication status | Published - Jan 1 2008 |
Keywords
- Bayesian estimation
- Bootstrap confidence intervals
- Generalized exponential distribution
- HPD intervals
- Importance sampling
- Maximum likelihood estimation
ASJC Scopus subject areas
- Statistics and Probability