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 | 
| 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 | 
| Reference manual: | GPCERF.html , GPCERF.pdf | 
| Vignettes: | A-Note-on-Choosing-Hyperparameters (source, R code) Developers-Guide (source, R code) GPCERF (source, R code) Nearest-neighbor-Gaussian-Processes (source, R code) Standard Gaussian Processes (source, R code) | 
| 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 | 
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