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Parameters Estimation in a Simple Linear Regression Using Rank Set Sampling

โœ Scribed by Dr. Hassen A. Muttlak

Publisher
John Wiley and Sons
Year
1995
Tongue
English
Weight
525 KB
Volume
37
Category
Article
ISSN
0323-3847

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โœฆ Synopsis

Ranked set sampling (RSS) as suggested by MCINTYRE (1952) and TAKAHASI and WAKIMOTO (1968) may be used to estimate the parameters of the simple regression line. The objective is to use the RSS method to increase the eficiency of the estimators relative to the simple random sampling (SRS) method. Estimators of the slope and intercept are considered. Computer simulated results are given, and an example using real data presented to illustrate the computations.

๐Ÿ“œ SIMILAR VOLUMES

Median ranked set sampling with concomit
Median ranked set sampling with concomitant variables and a comparison with ranked set sampling and regression estimators
โœ H. A. Muttlak ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 160 KB ๐Ÿ‘ 1 views

Ranked set sampling (RSS), as suggested by McIntyre (1952), assumes perfect ranking, i.e. without errors in ranking, but for most practical applications it is not easy to rank the units without errors in ranking. As pointed out by Dell and Clutter (1972) there will be a loss in precision due to the