hbamr: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'

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 default model is described in Bølstad (2023) <doi:10.1017/pan.2023.18>.

Version: 1.2.0
Depends: R (≥ 3.4.0)
Imports: dplyr, ggplot2, loo, matrixStats, methods, parallel, pbmcapply, plyr, RColorBrewer, Rcpp (≥ 1.0.7), RcppParallel (≥ 5.1.4), rlang, rstan (≥ 2.26.1), rstantools (≥ 2.2.0), stats, tidyr
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 1.0.7), RcppEigen (≥, RcppParallel (≥ 5.1.4), rstan (≥ 2.26.1), StanHeaders (≥ 2.26.22)
Suggests: data.table, knitr, rmarkdown
Published: 2023-09-25
Author: Jørgen Bølstad ORCID iD [aut, cre]
Maintainer: Jørgen Bølstad <jorgen.bolstad at stv.uio.no>
License: GPL (≥ 3)
URL: https://github.com/jbolstad/hbamr/
NeedsCompilation: yes
SystemRequirements: GNU make
CRAN checks: hbamr results


Reference manual: hbamr.pdf
Vignettes: Hierarchical Bayesian Aldrich-McKelvey Scaling in R via Stan


Package source: hbamr_1.2.0.tar.gz
Windows binaries: r-devel: hbamr_1.2.0.zip, r-release: hbamr_1.2.0.zip, r-oldrel: hbamr_1.2.0.zip
macOS binaries: r-release (arm64): hbamr_1.2.0.tgz, r-oldrel (arm64): hbamr_1.2.0.tgz, r-release (x86_64): hbamr_1.2.0.tgz, r-oldrel (x86_64): hbamr_1.1.6.tgz
Old sources: hbamr archive


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