Estimation of G-renewal process parameters as an ill-posed inverse problem

V. Krivtsov and O. Yevkin

Reliability Engineering and System Safety, 2013, vol. 115, issue C, 10-18

Abstract: Statistical estimation of G-renewal process parameters is an important estimation problem, which has been considered by many authors. We view this problem from the standpoint of a mathematically ill-posed, inverse problem (the solution is not unique and/or is sensitive to statistical error) and propose a regularization approach specifically suited to the G-renewal process. Regardless of the estimation method, the respective objective function usually involves parameters of the underlying life-time distribution and simultaneously the restoration parameter. In this paper, we propose to regularize the problem by decoupling the estimation of the aforementioned parameters. Using a simulation study, we show that the resulting estimation/extrapolation accuracy of the proposed method is considerably higher than that of the existing methods.

Keywords: G-renewal process; Underlying distribution; Monte Carlo simulation; Inverse problems; Regularization (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:115:y:2013:i:c:p:10-18

DOI: 10.1016/j.ress.2013.02.005

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