DOI

10.1016/j.jspi.2010.05.016

Abstract

This article proposes an adjusted empirical likelihood estimation (AMELE) method to model and analyze accelerated life testing data. This approach flexibly and rigorously incorporates distribution assumptions and regression structures by estimating equations within a semiparametric estimation framework. An efficient method is provided to compute the empirical likelihood estimates, and asymptotic properties are studied. Real-life examples and numerical studies demonstrate the advantage of the proposed methodology.

Document Type

Post-print Article

Publication Date

2011

Publisher Statement

Copyright © 2011 Elsevier B.V.

DOI: 10.1016/j.jspi.2010.05.016

The definitive version is available at: https://www.sciencedirect.com/science/article/pii/S0378375810002636

Full Citation:

Wang, Ni, Jye-Chi Lu, Di Chen, and Paul H. Kvam. "Adjusted Empirical Likelihood Models with Estimating Equations for Accelerated Life Tests." Journal of Statistical Planning and Inference141, no. 1 (2011): 140-155. doi:10.1016/j.jspi.2010.05.016.

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