Ranked set sampling, coherent rankings and size-biased permutations
β Scribed by G.P. Patil; A.K. Sinha; C. Taillie
- Book ID
- 104340412
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 619 KB
- Volume
- 63
- Category
- Article
- ISSN
- 0378-3758
No coin nor oath required. For personal study only.
β¦ Synopsis
The paper examines the effect of the set size upon the performance (reciprocal variance t of balanced ranked set sampling for estimation of a population mean. Performance is shown lo be monotone increasing with the set size for the wide class of ranking models that satisfy a property called coherence. This class includes perfect ranking as well as ranking by concomitant variable. Stochastic ranking models based upon size-biased permutations are also shown to satisJ~ coherence and, consequently, monotonicity. @ 1997 Elsevier Science B.V.
π SIMILAR VOLUMES
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
Ranked set sampling (RSS) was ΓΏrst used to obtain a more e cient estimator of the population mean, as compared to the one based on simple random sampling. This technique is useful when judgment ordering of a simple random sample (SRS) of small size can be done easily and fairly accurately, but exact