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".


Reference manual

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1.2.0 by Wanchuang Zhu, 8 months ago

Browse source code at https://github.com/cran/PAMA

Authors: Wanchuang Zhu [cre, aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports ExtMallows, mc2d, PerMallows, rankdist, Rcpp, stats

Suggests knitr, rmarkdown

Linking to Rcpp

See at CRAN