On conditional moments of progressively censored order statistics with a time constraint
Refereed conference paper presented and published in conference proceedings

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AbstractDifferent hybrid progressive censoring schemes, which are mixtures of Type-I censoring and Type-II progressively censoring schemes, have been proposed in the literature. These censoring schemes impose a time constraint on the life-testing experiment and the number of progressively censored order statistics observed before this time constraint is recorded. Conditional on the number of progressively censored order statistics being observed before the time constraint, a computational method for the conditional moments of progressively censored order statistics is discussed. Simple computational formulae are presented and these formulae are illustrated with examples when the underlying distributions are uniform and exponential. These results will be useful for the development of estimation methods such as the least squares estimation, best linear unbiased estimation and approximate maximum likelihood estimation methods and for deriving asymptotic distributions of the estimates of model parameters for Type-I hybrid progressively censored data.
All Author(s) ListTony Ng H.K., Duan F., Chan P.S.
Name of ConferenceInternational Conference in Honor of H.N. Nagaraja for His 60th Birthday, 2014
Start Date of Conference07/03/2014
End Date of Conference09/03/2014
Place of ConferenceDallas
Country/Region of ConferenceUnited States of America
Detailed descriptioned. by Pankaj K. Choudhary, Chaitra H. Nagaraja, Hon Keung Tony Ng.
Volume Number149
Pages55 - 71
LanguagesEnglish-United Kingdom
KeywordsApproximate maximum likelihood estimation, Best linear unbiased estimation, Hybrid censoring, Type-I censoring, Type-II censoring

Last updated on 2020-29-09 at 01:28