CRAN/E | hbamr

hbamr

Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'

Installation

About

Perform hierarchical Bayesian Aldrich-McKelvey scaling using Hamiltonian Monte Carlo via 'Stan'. Aldrich-McKelvey ('AM') scaling is a method for estimating the ideological positions of survey respondents and political actors on a common scale using positional survey data. The hierarchical versions of the Bayesian 'AM' model included in this package outperform other versions both in terms of yielding meaningful posterior distributions for respondent positions and in terms of recovering true respondent positions in simulations. The package contains functions for preparing data, fitting models, extracting estimates, plotting key results, and comparing models using cross-validation. The original version of the default model is described in Bølstad (2024) doi:10.1017/pan.2023.18.

Citation hbamr citation info
jbolstad.github.io/hbamr/
System requirements GNU make
Bug report File report

Key Metrics

Version 2.3.0
R ≥ 3.4.0
Published 2024-03-31 29 days ago
Needs compilation? yes
License GPL (≥ 3)
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Maintainer

Maintainer

Jørgen Bølstad

jorgen.bolstad@stv.uio.no

Authors

Jørgen Bølstad

aut / cre

Material

NEWS
Reference manual
Package source

Vignettes

Hierarchical Bayesian Aldrich-McKelvey Scaling in R via Stan

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hbamr archive

Depends

R ≥ 3.4.0

Imports

colorspace
dplyr
future
future.apply
ggplot2
loo
matrixStats
methods
parallel
plyr
progressr
RColorBrewer
Rcpp ≥ 1.0.7
RcppParallel ≥ 5.1.4
rlang
rstan ≥2.26.1
rstantools ≥ 2.2.0
stats
tidyr

Suggests

data.table
knitr
rmarkdown

LinkingTo

BH ≥ 1.66.0
Rcpp ≥ 1.0.7
RcppEigen ≥ 0.3.3.9.1
RcppParallel ≥ 5.1.4
rstan ≥ 2.26.1
StanHeaders ≥2.26.22