Fourth-order kernel method for simple linear degradation model |
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Authors: | Osama H Arif |
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Institution: | Department of Statistics—Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia |
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Abstract: | Degradation analysis is a useful technique when life tests result in few or even no failures. The degradation measurements are recorded over time and the estimation of time-to-failure distribution plays a vital role in degradation analysis. The parametric method to estimate the time-to-failure distribution assumed a specific parametric model with known shape for the random effects parameter. To avoid any assumption about the model shape, a nonparametric method can be used. In this paper, we suggest to use the nonparametric fourth-order kernel method to estimate the time-to-failure distribution and its percentiles for the simple linear degradation model. The performances of the proposed method are investigated and compared with the classical kernel; maximum likelihood and ordinary least squares methods via simulation technique. The numerical results show the good performance of the fourth-order kernel method and demonstrate its superiority over the parametric method when there is no information about the shape of the random effect parameter distribution. |
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Keywords: | Classical kernel method Degradation Failure time Fourth-order kernel method Maximum likelihood Ordinary least square |
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