GPCERF: Gaussian Processes for Estimating Causal Exposure Response Curves
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 |
| Author: | Naeem Khoshnevis 
[aut] (HUIT),
Boyu Ren [aut,
cre] (McLean Hospital),
Tanujit Dey [ctb]
(HMS),
Danielle Braun
[aut] (HSPH) |
| Maintainer: | Boyu Ren <bren at mgb.org> |
| 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 |
Documentation:
| Reference manual: | GPCERF.pdf |
| Vignettes: |
A-Note-on-Choosing-Hyperparameters Developers-Guide GPCERF Nearest-neighbor-Gaussian-Processes Standard Gaussian Processes |
Downloads:
| Package source: | GPCERF_0.2.4.tar.gz |
| Windows binaries: | r-devel: GPCERF_0.2.4.zip, r-release: GPCERF_0.2.4.zip, r-oldrel: GPCERF_0.2.4.zip |
| macOS binaries: | r-release (arm64): GPCERF_0.2.4.tgz, r-oldrel (arm64): GPCERF_0.2.4.tgz, r-release (x86_64): GPCERF_0.2.4.tgz, r-oldrel (x86_64): GPCERF_0.2.4.tgz |
| Old sources: | GPCERF archive |
Linking:
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