Package: hbamr 2.3.2

Jørgen Bølstad

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 original version of the default model is described in Bølstad (2024) <doi:10.1017/pan.2023.18>.

Authors:Jørgen Bølstad [aut, cre]

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hbamr.pdf |hbamr.html
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NEWS

# Install 'hbamr' in R:
install.packages('hbamr', repos = c('https://jbolstad.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jbolstad/hbamr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • LC1980 - 1980 Liberal-Conservative Scales
  • LC2012 - 2012 Liberal-Conservative Scales

On CRAN:

bayesianbayesian-inferenceideal-point-estimationstansurvey-analysis

5.20 score 2 stars 412 downloads 12 exports 69 dependencies

Last updated 5 months agofrom:a3cde61174. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-win-x86_64NOTENov 22 2024
R-4.5-linux-x86_64NOTENov 22 2024
R-4.4-win-x86_64NOTENov 22 2024
R-4.4-mac-aarch64NOTENov 22 2024
R-4.3-win-x86_64NOTENov 22 2024
R-4.3-mac-aarch64NOTENov 22 2024

Exports:fbamget_estget_plot_datahbamhbam_cvplot_by_groupplot_over_selfplot_respondentsplot_stimuliprep_dataprep_data_cvshow_code

Dependencies:abindbackportsBHcallrcheckmateclicodetoolscolorspacecpp11descdigestdistributionaldplyrfansifarverfuturefuture.applygenericsggplot2globalsgluegridExtragtableinlineisobandlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxprogressrpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Hierarchical Bayesian Aldrich-McKelvey Scaling in R via Stan

Rendered fromhbamr.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2024-03-31
Started: 2023-02-05