Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1150113 | Journal of Statistical Planning and Inference | 2011 | 16 Pages |
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Ni Wang, Jye-Chi Lu, Di Chen, Paul H. Kvam,