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https://doi.org/10.1016/S0378-3758(00)00140-3
Title: | Ranked-set sampling with regression-type estimators | Authors: | Chen, Z. | Keywords: | 62D05 62G20 62G30 Asymptotic distribution Concomitant variable Minimum variance Ranked set sampling Regression-type estimator |
Issue Date: | Jan-2001 | Citation: | Chen, Z. (2001-01). Ranked-set sampling with regression-type estimators. Journal of Statistical Planning and Inference 92 (1-2) : 181-192. ScholarBank@NUS Repository. https://doi.org/10.1016/S0378-3758(00)00140-3 | Abstract: | Ranked set sampling (RSS) is a sampling scheme to reduce cost and increase efficiency in situations where the measurement of a survey variable is costly and/or time-consuming but ranking of sampled items relating to the survey variable can be easily done by certain other means. When a concomitant variable is readily available, the concomitant variable can be employed to aid in both sampling and estimation. Regression-type estimators making use of concomitant variables have been proposed in the literature. In this article, we study further the properties of the regression-type estimators and propose a modified RSS regression estimator which improves the available estimators. Comparison among the proposed and available estimators are made both theoretically and by simulation. Asymptotic distribution of the regression-type estimators are established and hence construction of confidence intervals and hypothesis testing based on these estimators are made possible. © 2001 Elsevier Science B.V. | Source Title: | Journal of Statistical Planning and Inference | URI: | http://scholarbank.nus.edu.sg/handle/10635/105322 | ISSN: | 03783758 | DOI: | 10.1016/S0378-3758(00)00140-3 |
Appears in Collections: | Staff Publications |
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