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Estimation of the Weibull Distribution Parameters and Reliability Using Kernel and Bayes Approaches |
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PP: 1125-1132 |
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doi:10.18576/isl/120304
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Author(s) |
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M. Maswadah,
M. Seham,
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Abstract |
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| A new estimation technique based on the non-parametric kernel density
estimation is introduced as an alternative and reliable technique for estimation in life testing models. This technique estimates the density functions of the parameters and reliability directly from the data without any prior assumptions about the underlying distribution parameters. The efficiency of this technique has been studied comparing
to the Bayesian estimation of the parameters and reliability of the Weibull distribution based on the non-informative, informative and the informative conjugate priors, via Monte Carlo simulations, which indicated the robustness of the proposed method than the Bayesian
approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper. |
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