gpss: Gaussian Processes for Social Science
Provides Gaussian process (GP) regression tools for social
science inference problems. GPs combine flexible nonparametric
regression with principled uncertainty quantification: rather than
committing to a single model fit, the posterior reflects lesser
knowledge at the edge of or beyond the observed data, where other
approaches become highly model-dependent. The package reduces
user-chosen hyperparameters from three to zero and supplies
convenience functions for regression discontinuity (gp_rdd()),
interrupted time-series (gp_its()), and general GP fitting
(gpss(), gp_train(), gp_predict()). Methods are described in
Cho, Kim, and Hazlett (2026) <doi:10.1017/pan.2026.10032>.
| Version: |
1.0.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp (≥ 1.0.14), Matrix, ggplot2, rlang |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
MASS, posterior, testthat (≥ 3.0.0) |
| Published: |
2026-04-08 |
| DOI: |
10.32614/CRAN.package.gpss |
| Author: |
Soonhong Cho [aut],
Doeun Kim  [aut],
Chad Hazlett [aut, cre] |
| Maintainer: |
Chad Hazlett <chazlett at ucla.edu> |
| BugReports: |
https://github.com/doeun-kim/gpss/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://doeunkim.org/gpss/, https://github.com/doeun-kim/gpss |
| NeedsCompilation: |
yes |
| Materials: |
README, NEWS |
| CRAN checks: |
gpss results |
Documentation:
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