A- and D-optimal progressive Type-II censoring designs based on Fisher information

Abstract

Fisher information about multiple parameters in a progressively Type-II censored sample is discussed. A representation of the Fisher information matrix in terms of the hazard rate of the baseline distribution is established which can be used for efficient computation of the Fisher information. This expression generalizes a result of Zheng and Park [On the Fisher information in multiply censored and progressively censored data, Comm. Statist. Theory Methods 33 (2004), pp. 1821–1835] for Fisher information about a single parameter. The result is applied to identify A- and D-optimal censoring plans in a progressively Type-II censored experiment. For illustration, extreme value, normal, and Lomax distributions are considered.

Keywords:

• Fisher information
• progressive censoring
• hazard rate
• optimal progressive censoring designs
• extreme value distribution
• normal distribution
• Lomax distribution

Acknowledgements

This research was funded by the Excellence Initiative of the German federal and state governments. We are grateful to a reviewer for comments and suggestions which led to an improved presentation.