Comparison Of Maximum Likelihood And Bayes Estimators Under Symmetric And Asymmetric Loss Functions By Means Of Tierney Kadane’s Approximation For Weibull Distribution
| Autor: | GENCER, Gülcan, GENCER, Kerem |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Volume: 14, Issue: 2 69-78 Turkish Journal of Science and Technology |
| ISSN: | 1308-9080 1308-9099 |
| Popis: | In this study, it is considered the problemof comparing the performances of the Maximum Likelihood (ML) and Bayesestimators under symmetric and asymmetric loss function for the unknown parameters of Weibulldistribution. ML estimators are computed by using the Newton Raphson method. Bayesianestimations under Squared, Linex and General Entropy loss functions by usingJeffrey’s extension prior are introduced with Tierney Kadane approximation forWeibull distribution. For different sample sizes, estimators are compared toobtain the best estimator in terms of mean squared errors using a Monte Carlosimulation study. |
| Databáze: | OpenAIRE |
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