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Title: Statistical inference for the extreme value distribution under adaptive Type-II progressive censoring schemes
Authors: Ye, Z.-S.
Chan, P.-S.
Xie, M. 
Ng, H.K.T.
Keywords: adaptive type-II progressive censoring
confidence interval
extreme value distribution
information matrix
the bootstrap
Issue Date: May-2014
Citation: Ye, Z.-S., Chan, P.-S., Xie, M., Ng, H.K.T. (2014-05). Statistical inference for the extreme value distribution under adaptive Type-II progressive censoring schemes. Journal of Statistical Computation and Simulation 84 (5) : 1099-1114. ScholarBank@NUS Repository.
Abstract: Adaptive Type-II progressive censoring schemes have been shown to be useful in striking a balance between statistical estimation efficiency and the time spent on a life-testing experiment. In this article, some general statistical properties of an adaptive Type-II progressive censoring scheme are first investigated. A bias correction procedure is proposed to reduce the bias of the maximum likelihood estimators (MLEs). We then focus on the extreme value distributed lifetimes and derive the Fisher information matrix for the MLEs based on these properties. Four different approaches are proposed to construct confidence intervals for the parameters of the extreme value distribution. Performance of these methods is compared through an extensive Monte Carlo simulation. © 2013 © 2013 Taylor & Francis.
Source Title: Journal of Statistical Computation and Simulation
ISSN: 00949655
DOI: 10.1080/00949655.2012.740481
Appears in Collections:Staff Publications

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