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 by a considerable margin 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 models in
this package are described in: Bølstad (forthcoming) ”Hierarchical Bayesian Aldrich-McKelvey
Scaling”, Political Analysis.
| Version: |
1.1.1 |
| Depends: |
R (≥ 3.4.0) |
| Imports: |
dplyr, ggplot2, loo, matrixStats, methods, parallel, pbmcapply, plyr, RColorBrewer, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rlang, rstan (≥ 2.18.1), rstantools (≥ 2.2.0), stats, tidyr |
| LinkingTo: |
BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥
2.18.0) |
| Suggests: |
data.table, knitr, rmarkdown |
| Published: |
2023-04-24 |
| Author: |
Jørgen Bølstad 
[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 |
Documentation:
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