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Provides tools for Ranked Set Sampling (RSS) analysis, data import, statistical estimation, and comparison with Simple Random Sampling (SRS). The package offers a complete workflow from 'Excel' and CSV data import and cleaning to RSS implementation, efficiency evaluation, visualization, and automated reporting. Intelligent ranking procedures based on correlation analysis, regression models, and machine learning methods are included to address imperfect ranking commonly encountered in practical RSS applications. Monte Carlo simulation tools are provided for evaluating estimator performance under different sampling scenarios. Ranked Set Sampling was originally introduced by McIntyre (1952) <doi:10.2307/3001960> as an efficient alternative to simple random sampling when ranking information is available at low cost. The package supports researchers, statisticians, and practitioners working in agricultural, environmental, biological, and other applied sciences.
| Version: | 0.2.4 |
| Depends: | R (≥ 4.3.0) |
| Imports: | ggplot2, readxl, rlang, stats, utils |
| Published: | 2026-07-09 |
| DOI: | 10.32614/CRAN.package.KlerRSS |
| Author: | Khalid Ul Islam Rather [aut, cre] |
| Maintainer: | Khalid Ul Islam Rather <drkhalidulislam at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | KlerRSS results |
| Reference manual: | KlerRSS.html , KlerRSS.pdf |
| Package source: | KlerRSS_0.2.4.tar.gz |
| Windows binaries: | r-devel: KlerRSS_0.2.4.zip, r-release: KlerRSS_0.2.4.zip, r-oldrel: KlerRSS_0.2.4.zip |
| macOS binaries: | r-release (arm64): KlerRSS_0.2.4.tgz, r-oldrel (arm64): KlerRSS_0.2.4.tgz, r-release (x86_64): KlerRSS_0.2.4.tgz, r-oldrel (x86_64): KlerRSS_0.2.4.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.