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http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200201539

Kurzfassung in Englisch

Progressive Type-II censoring was introduced by Cohen (1963) and has since been
the topic of much research. The question stands whether it is sensible to use this
sampling plan by design, instead of regular Type-II right censoring. We introduce
an asymptotic progressive censoring model, and find optimal censoring schemes for
location-scale families. Our optimality criterion is the determinant of the 2x2 covariance
matrix of the asymptotic best linear unbiased estimators. We present an explicit
expression for this criterion, and conditions for its boundedness. By means of numerical
optimization, we determine optimal censoring schemes for the extreme value,
the Weibull and the normal distributions. In many situations, it is shown that these
progressive schemes significantly improve upon regular Type-II right censoring.

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