This paper proposes procedures to provide confidence intervals (CIs) for reliability in stress–strength models, considering the particular case of a bivariate normal set-up. The suggested CIs are obtained by employing either asymptotic variances of maximum-likelihood estimators or a bootstrap procedure. The coverage and the accuracy of these intervals are empirically checked through a simulation study and compared with those of another proposal in the literature. An application to real data is provided.
Interval estimators for reliability : the bivariate normal case / A. Barbiero. - In: JOURNAL OF APPLIED STATISTICS. - ISSN 0266-4763. - 39:3(2012), pp. 501-512.
Interval estimators for reliability : the bivariate normal case
A. BarbieroPrimo
2012
Abstract
This paper proposes procedures to provide confidence intervals (CIs) for reliability in stress–strength models, considering the particular case of a bivariate normal set-up. The suggested CIs are obtained by employing either asymptotic variances of maximum-likelihood estimators or a bootstrap procedure. The coverage and the accuracy of these intervals are empirically checked through a simulation study and compared with those of another proposal in the literature. An application to real data is provided.File | Dimensione | Formato | |
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