A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Partial ranked set sampling design
In many environmental studies, the main focus is on observational economy, that is, to obtain data on the basis of cost‐effective and efficient sampling methods. In this paper, we propose a partial ranked set sampling (PRSS) method for estimation of population mean, median and variance. On the basis of perfect and imperfect rankings, Monte Carlo simulations from symmetric and asymmetric distributions are used to evaluate the effectiveness of the proposed estimators. It is found that the estimators under PRSS are more efficient than the estimators based on simple random sampling. The procedure is illustrated with a case study using a real data set. Copyright © 2013 John Wiley & Sons, Ltd.
Partial ranked set sampling design
In many environmental studies, the main focus is on observational economy, that is, to obtain data on the basis of cost‐effective and efficient sampling methods. In this paper, we propose a partial ranked set sampling (PRSS) method for estimation of population mean, median and variance. On the basis of perfect and imperfect rankings, Monte Carlo simulations from symmetric and asymmetric distributions are used to evaluate the effectiveness of the proposed estimators. It is found that the estimators under PRSS are more efficient than the estimators based on simple random sampling. The procedure is illustrated with a case study using a real data set. Copyright © 2013 John Wiley & Sons, Ltd.
Partial ranked set sampling design
Haq, Abdul (author) / Brown, Jennifer (author) / Moltchanova, Elena (author) / Al‐Omari, Amer Ibrahim (author)
Environmetrics ; 24 ; 201-207
2013-05-01
7 pages
Article (Journal)
Electronic Resource
English
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