PAMA: Rank Aggregation with Partition Mallows Model

Rank aggregation aims to achieve a better ranking list given multiple observations. 'PAMA' implements Partition-Mallows model for rank aggregation where the rankers' quality are different. Both Bayesian inference and Maximum likelihood estimation (MLE) are provided. It can handle partial list as well. When covariates information is available, this package can make inference by incorporating the covariate information. More information can be found in the paper "Integrated Partition-Mallows Model and Its Inference for Rank Aggregation".

Version:	1.2.0
Depends:	R (≥ 3.1.0)
Imports:	ExtMallows, mc2d, PerMallows, rankdist, Rcpp, stats
LinkingTo:	Rcpp
Suggests:	knitr, rmarkdown
Published:	2021-05-06
Author:	Wanchuang Zhu [cre, aut]
Maintainer:	Wanchuang Zhu <andy.chou.sub at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
Materials:	README
CRAN checks:	PAMA results

Documentation:

Reference manual:

PAMA.pdf

Downloads:

Package source:	PAMA_1.2.0.tar.gz
Windows binaries:	r-devel: PAMA_1.2.0.zip, r-release: PAMA_1.2.0.zip, r-oldrel: PAMA_1.2.0.zip
macOS binaries:	r-release (arm64): PAMA_1.2.0.tgz, r-oldrel (arm64): PAMA_1.2.0.tgz, r-release (x86_64): PAMA_1.2.0.tgz, r-oldrel (x86_64): PAMA_1.2.0.tgz
Old sources:	PAMA archive

Linking:

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