Progressively Type-II censored competing risks data from Lomax distributions

Authors:
Erhard Cramer;Anja Bettina Schmiedt
Affiliations:
-;-
Venue:
Computational Statistics & Data Analysis
Year:
2011

Citing 7
Cited 1

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Abstract

A competing risks model based on Lomax distributions is considered under progressive Type-II censoring. Maximum likelihood estimates for the distribution parameters are established. Moreover, the expected Fisher information matrix is computed and optimal Fisher information based censoring plans are discussed. In particular, it turns out that the optimal censoring scheme depends on the particular parametrization of the Lomax distributions.