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. 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". The paper is not yet published.

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Description file content

Package
PAMA
Title
Rank Aggregation with Partition Mallows Model
Version
0.1.0
Description
Rank aggregation aims to achieve a better ranking list given multiple observations. 'PAMA' implements Partition-Mallows model for rank aggregation. 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". The paper is not yet published.
Depends
R (>= 3.1.0), PerMallows, mc2d, stats
Imports
License
GPL (>= 2)
Encoding
UTF-8
LazyData
true
RoxygenNote
7.0.1
Suggests
knitr, rmarkdown
NeedsCompilation
no
Packaged
2020-01-09 22:11:11 UTC; wanchuangzhu
Author
Wanchuang Zhu [cre, aut]
Maintainer
Wanchuang Zhu
Repository
CRAN
Date/Publication
2020-01-13 16:20:05 UTC

install.packages('PAMA')

0.1.0

11 days ago

Wanchuang Zhu

GPL (>= 2)

Depends on

R (>= 3.1.0), PerMallows, mc2d, stats

Suggests

knitr, rmarkdown

Discussions