A new extension of moment exponential distribution, called exponentiated moment exponential distribution
(EMED), was recently introduced by Hasnain [14]. Based on lower generalized order statistics, we
first derive the explicit expressions as well as recurrence relations for single and product moments of lower
generalized order statistics and we use these results to compute the means, variances and coefficients of
skewness and kurtosis of EMED. Further, using a recurrence relation for single moment, we obtain characterization
of EMED. Next we obtain the maximum likelihood estimators of the unknown parameters
and the approximate confidence intervals of the EMED. Finally, we consider Bayes estimation under the
symmetric and asymmetric loss functions using gamma priors for both shape and scale parameters. We
have are also derived the Bayes interval of this distribution. Monte Carlo simulations are performed to
compare the performances of the proposed methods.
explicit expression Recurrence relation Lower generalized order statistics Order statistics Record values Exponentiated moment exponential distribution Bayes estimator General entropy loss function Maximum likelihood estimator
Primary Language | English |
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Journal Section | Articles |
Authors | |
Publication Date | April 15, 2016 |
Submission Date | March 4, 2015 |
Published in Issue | Year 2016 Volume: 4 Issue: 1 |
The published articles in MSAEN are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.