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Generate situation for voting simulation - R package

The package voteSim aims at providing several models for simulating distributions of evaluations given by voters on candidates concerning a voting situation within an evaluation-based perspective. The proposed simulation functions cover Uniform, Truncated Normal, Beta, Dirichlet, Multinormal, copula-based and spatial models as developed in the reference article. Basically a function is proposed for each model which produces a matrix with candidates in rows and voters in columns.

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Install

install.packages('voteSim')

Monthly Downloads

42

Version

0.1.1

License

GPL-3

Maintainer

Antoine Rolland

Last Published

December 19th, 2023

Functions in voteSim (0.1.1)

voteSim-package

voteSim: Generate Simulated Data for Voting Rules using Evaluations
DistToScores

Distance to score
distance

Distance formula
generate_binomial

Generate binomial scores
generate_dirichlet

Generate multinomial scores
distance_to_pref

Distance formula
generate_multinom

Generate multinomial scores
generate_beta

Generates a simulation of voting according to a beta law, returns voters preferences
ScoresToDist

Score to distance
generate_discrete_copula_based

Discrete Copula based scores
icdf

Generalized inverse of the empirical cumulative function.
preferences_to_ranks

Preferences_to_ranks
rename_rows

Rename_rows
generate_beta_binomial

Generate beta-binomial scores
generate_unif_continuous

Generates a simulation of voting according to a uniform law, returns voters preferences
generate_unif_disc

Generate uniform discrete scores
generate_norm

Generate truncated normal scores
generate_spatial

Generate spatial simulation