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Easily compute an aggregate ranking (also called a median ranking or a consensus ranking) according to the axiomatic approach presented by Cook et al. (2007). This approach minimises the number of violations between all candidate consensus rankings and all input (partial) rankings, and draws on a branch and bound algorithm and a heuristic algorithm to drastically improve speed. The package also provides an option to bootstrap a consensus ranking based on resampling input rankings (with replacement). Input rankings can be either incomplete (partial) or complete. Reference: Cook, W.D., Golany, B., Penn, M. and Raviv, T. (2007) <doi:10.1016/j.cor.2005.05.030>.
Version: | 0.0.1 |
Depends: | R (≥ 2.10) |
Suggests: | knitr |
Published: | 2020-08-31 |
DOI: | 10.32614/CRAN.package.RankAggregator |
Author: | Jay Burns [aut, cre], Adam Butler [aut] |
Maintainer: | Jay Burns <jay.burns at sruc.ac.uk> |
License: | GPL-3 |
NeedsCompilation: | no |
Citation: | RankAggregator citation info |
CRAN checks: | RankAggregator results |
Reference manual: | RankAggregator.pdf |
Package source: | RankAggregator_0.0.1.tar.gz |
Windows binaries: | r-devel: RankAggregator_0.0.1.zip, r-release: RankAggregator_0.0.1.zip, r-oldrel: RankAggregator_0.0.1.zip |
macOS binaries: | r-release (arm64): RankAggregator_0.0.1.tgz, r-oldrel (arm64): RankAggregator_0.0.1.tgz, r-release (x86_64): RankAggregator_0.0.1.tgz, r-oldrel (x86_64): RankAggregator_0.0.1.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.