Order restricted statistical inference for scale parameters based on sequential order statistics

In the situation of a multi-sample experiment consisting of differently equipped sequential k-out-of- n systems, scale parameters of underlying distributions from a general location-scale family of distributions are estimated under an order restriction. In each sample, the case of missing the smalle...

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Bibliographic Details
Published in:Journal of statistical planning and inference 2009-09, Vol.139 (9), p.2963-2969
Main Authors: Beutner, E., Kamps, U.
Format: Article
Language:English
Subjects:
Distribution theory
Exact sciences and technology
General topics
Location-scale family
Mathematics
Nonparametric inference
Order restricted hypothesis testing
Order restricted maximum likelihood estimation
Probability and statistics
Probability theory and stochastic processes
Profile likelihood
Sciences and techniques of general use
Sequential k-out-of- n model
Sequential order statistics
Statistics
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Summary:In the situation of a multi-sample experiment consisting of differently equipped sequential k-out-of- n systems, scale parameters of underlying distributions from a general location-scale family of distributions are estimated under an order restriction. In each sample, the case of missing the smallest observations is included. Moreover, based on a profile likelihood a homogeneity test against an ordered alternative is proposed and analyzed. This work extends an approach of Bhattacharya [2007. Testing for ordered failure rates under general progressive censoring. J. Statist. Plann. Inference 137, 1775–1786] in the progressive Type-II censoring framework.
ISSN:0378-3758
1873-1171
DOI:10.1016/j.jspi.2009.01.017