Approximate bayesian estimates of weibull parameters with Lindley’s method
One of the most important lifetime distributions that is used for modelling and analysing data in clinical, life sciences and engineering is the Weibull distribution. The main objective of this paper was to determine the best estimator for the two-parameter Weibull distribution. The methods under co...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Kebangsaan Malaysia
2014
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| Online Access: | http://journalarticle.ukm.my/7684/ http://journalarticle.ukm.my/7684/ http://journalarticle.ukm.my/7684/1/19_Chris_Bambey.pdf |
| Summary: | One of the most important lifetime distributions that is used for modelling and analysing data in clinical, life sciences and engineering is the Weibull distribution. The main objective of this paper was to determine the best estimator for the two-parameter Weibull distribution. The methods under consideration are the frequentist maximum likelihood estimator, least square regression estimator and the Bayesian estimator by using two loss functions, which are squared error and linear exponential. Lindley approximation is used to obtain the Bayes estimates. Comparisons are made through simulation study to determine the performance of these methods. Based on the results obtained from this simulation study the Bayesian approach used in estimating the Weibull parameters under linear exponential loss function is found to be superior as compared to the conventional maximum likelihood and least squared methods. |
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