Journal article
Optimal Progressive Type-II Censoring Schemes for Nonparametric Confidence Intervals of Quantiles
Abstract
In this article, optimal progressive censoring schemes are examined for the nonparametric confidence intervals of population quantiles. The results obtained can be universally applied to any continuous probability distribution. By using the interval mass as an optimality criterion, the optimization process is free of the actual observed values from the sample and needs only the initial sample size n and the number of complete failures m. Using …
Authors
Balakrishnan N; Han D
Journal
Communications in Statistics - Simulation and Computation, Vol. 36, No. 6, pp. 1247–1262
Publisher
Taylor & Francis
Publication Date
November 5, 2007
DOI
10.1080/03610910701569184
ISSN
0361-0918