GPCERF: Gaussian Processes for Estimating Causal Exposure Response Curves (original) (raw)
Provides a non-parametric Bayesian framework based on Gaussian process priors for estimating causal effects of a continuous exposure and detecting change points in the causal exposure response curves using observational data. Ren, B., Wu, X., Braun, D., Pillai, N., & Dominici, F.(2021). "Bayesian modeling for exposure response curve via gaussian processes: Causal effects of exposure to air pollution on health outcomes." arXiv preprint <doi:10.48550/arXiv.2105.03454>.
| Version: | 0.2.4 |
|---|---|
| Depends: | R (≥ 3.5.0) |
| Imports: | parallel, xgboost, stats, MASS, spatstat.geom, logger, Rcpp, RcppArmadillo, ggplot2, cowplot, rlang, Rfast, SuperLearner, wCorr |
| LinkingTo: | RcppArmadillo, Rcpp |
| Suggests: | rmarkdown, knitr, testthat (≥ 3.0.0) |
| Published: | 2024-04-15 |
| DOI: | 10.32614/CRAN.package.GPCERF |
| Author: | Naeem Khoshnevis  [aut] (AFFILIATION: HUIT), Boyu Ren [aut, cre] (AFFILIATION: McLean Hospital), Tanujit Dey [ctb] (AFFILIATION: HMS), Danielle Braun [aut] (AFFILIATION: HSPH) |
| Maintainer: | Boyu Ren |
| BugReports: | https://github.com/NSAPH-Software/GPCERF/issues |
| License: | GPL (≥ 3) |
| Copyright: | Harvard University |
| URL: | https://github.com/NSAPH-Software/GPCERF |
| NeedsCompilation: | yes |
| Language: | en-US |
| Citation: | GPCERF citation info |
| Materials: | README, NEWS |
| CRAN checks: | GPCERF results |
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