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Estimation of average milk yield using ranked set sampling
Author(s) -
AlSaleh Mohammad Fraiwan,
AlShrafat Khalaf
Publication year - 2001
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.478
Subject(s) - rss , statistics , simple random sample , sampling (signal processing) , estimator , ranking (information retrieval) , mathematics , set (abstract data type) , sampling design , computer science , artificial intelligence , medicine , population , environmental health , filter (signal processing) , computer vision , programming language , operating system
With the aim of investigating the effectiveness of ranked set sampling (RSS) technique for improving the sampling precision of estimating the average milk yield, a study is conducted on a field of (402) sheep in East Jordan. It appears that the relative saving of sampling units when using RSS with set size (3) is between 32% and 44% compared to simple random sampling (SRS). The precision of the estimator obtained using RSS with respect to that obtained using SRS is calculated for both perfect and visual ranking. Copyright © 2001 John Wiley & Sons, Ltd.