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PAMA (version 0.1.1)

Rank Aggregation with Partition Mallows Model

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.

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Version

Install

install.packages('PAMA')

Monthly Downloads

60

Version

0.1.1

License

GPL (>= 2)

Maintainer

Wanchuang Zhu

Last Published

April 9th, 2020

Functions in PAMA (0.1.1)

PAMA.PL

This function implements Bayesian inference of PAMA model with partial lists.
PAMA.B

This function implements Bayesian inference of PAMA model.
NBANFL

Dataset of NBA and NFL.
PAMA.F

This function implements Maximum Likelihood estimation of PAMA model.
PAMA.Cov

This function implements Bayesian inference of PAMA model with covariates.