Bayesian approach on the generalized exponential distribution in the presence of outliers. (English) Zbl 05902627
Summary: The maximum likelihood and the Bayes estimators are derived for sample from the Generalized-Exponential distribution in the presence of \(k\) outliers. These estimators are obtained using Newton-Raphson method and Lindley’s approximation (L-approximation). The proposed Bayes estimators are obtained under symmetric and asymmetric loss functions. These estimators are compared empirically using Monte Carlo simulation, when all the parameters are unknown.
MSC:
| 62-XX | Statistics |
Keywords:
Bayesian inference; maximum likelihood estimator; LINEX loss function; generalized-exponential distribution; outliers; Lindley’s approximation; Newton-Raphson method; Monte-Carlo simulationReferences:
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