BAYESIAN APPROACH IN ESTIMATION OF SHAPE PARAMETER OF THE EXPONENTIATED MOMENT EXPONENTIAL DISTRIBUTION
In this paper, Bayes estimators of the unknown shape parameter of the exponentiated moment exponential distribution (EMED)have been derived by using two informative (gamma and chi-square) priors and two non-informative (Jeffrey’s and uniform) priors under different loss functions, namely, Squared Er...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2018-06-01
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| Series: | Journal of Statistical Theory and Applications (JSTA) |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25898355/view |
| Summary: | In this paper, Bayes estimators of the unknown shape parameter of the exponentiated moment exponential distribution (EMED)have been derived by using two informative (gamma and chi-square) priors and two non-informative (Jeffrey’s and uniform) priors under different loss functions, namely, Squared Error Loss function, Entropy loss function and precautionary Loss function. The Maximum likelihood estimator (MLE) is obtained. Also, we used two real life data sets to illustrate the result derived. |
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| ISSN: | 1538-7887 |