RSSampling: Ranked Set Sampling

Ranked set sampling (RSS) is introduced as an advanced method for data collection which is substantial for the statistical and methodological analysis in scientific studies by McIntyre (1952) (reprinted in 2005) <doi:10.1198/000313005X54180>. This package introduces the first package that implements the RSS and its modified versions for sampling. With 'RSSampling', the researchers can sample with basic RSS and the modified versions, namely, Median RSS, Extreme RSS, Percentile RSS, Balanced groups RSS, Double RSS, L-RSS, Truncation-based RSS, Robust extreme RSS. The 'RSSampling' also allows imperfect ranking using an auxiliary variable (concomitant) which is widely used in the real life applications. Applicants can also use this package for parametric and nonparametric inference such as mean, median and variance estimation, regression analysis and some distribution-free tests where the the samples are obtained via basic RSS.

Version:	1.0
Imports:	LearnBayes, stats
Published:	2018-03-19
DOI:	10.32614/CRAN.package.RSSampling
Author:	Busra Sevinc, Bekir Cetintav, Melek Esemen, Selma Gurler
Maintainer:	Busra Sevinc <busra.sevincc at gmail.com>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	RSSampling results

Documentation:

Reference manual:

RSSampling.pdf

Downloads:

Package source:	RSSampling_1.0.tar.gz
Windows binaries:	r-devel: RSSampling_1.0.zip, r-release: RSSampling_1.0.zip, r-oldrel: RSSampling_1.0.zip
macOS binaries:	r-release (arm64): RSSampling_1.0.tgz, r-oldrel (arm64): RSSampling_1.0.tgz, r-release (x86_64): RSSampling_1.0.tgz, r-oldrel (x86_64): RSSampling_1.0.tgz

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