General Ranked Set Sampling with Cost Considerations
Nahhas, Wolfe, and Chen (2002, Biometrics58, 964–971) considered optimal set size for ranked set sampling (RSS) with fixed operational costs. This framework can be very useful in practice to determine whether RSS is beneficial and to obtain the optimal set size that minimizes the variance of the population estimator for a fixed total cost. In this article, we propose a scheme of general RSS in which more than one observation can be taken from each ranked set. This is shown to be more cost-effective in some cases when the cost of ranking is not so small. We demonstrate using the example in Nahhas, Wolfe, and Chen (2002, Biometrics58, 964–971), by taking two or more observations from one set even with the optimal set size from the RSS design can be more beneficial.
Document Type: Research Article
Affiliations: Department of Statistics and Applied Probability, National University of Singapore, Singapore 119260
Publication date: 2004-06-01