Munich Personal RePEc Archive

Estimation and model selection for left-truncated and right-censored lifetime data with application to electric power transformers analysis

Emura, Takeshi and Shiu, Shau-Kai (2014): Estimation and model selection for left-truncated and right-censored lifetime data with application to electric power transformers analysis. Forthcoming in: Communications in Statistics - Simulation and Computation

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Abstract

In lifetime analysis of electric transformers, the maximum likelihood estimation has been proposed with the EM algorithm. However, it is not clear whether the EM algorithm offers a better solution compared to the simpler Newton-Raphson algorithm. In this paper, the first objective is a systematic comparison of the EM algorithm with the Newton-Raphson algorithm in terms of convergence performance. The second objective is to examine the performance of Akaike's information criterion (AIC) for selecting a suitable distribution among candidate models via simulations. These methods are illustrated through the electric power transformer dataset.

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