DESCRIPTION

Package: GPCERF
Title: Gaussian Processes for Estimating Causal Exposure Response Curves
Version: 0.2.4
Authors@R: c(
    person("Naeem", "Khoshnevis", email = "nkhoshnevis@g.harvard.edu",
           role=c("aut"), 
           comment = c(ORCID = "0000-0003-4315-1426", AFFILIATION="HUIT")),
    person("Boyu", "Ren", email = "bren@mgb.org",
           role= c("aut","cre"),            
           comment = c(ORCID = "0000-0002-5300-1184", AFFILIATION="McLean Hospital")),
    person("Tanujit", "Dey", email = "tdey@bwh.harvard.edu",
           role= c("ctb"),            
           comment = c(ORCID = "0000-0001-5559-211X", AFFILIATION="HMS")),
    person("Danielle","Braun", email = "dbraun@hsph.harvard.edu",
           role=c("aut"),     
           comment = c(ORCID = "0000-0002-5177-8598", AFFILIATION="HSPH")))
Maintainer: Boyu Ren <bren@mgb.org>
Description: 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 <arXiv:2105.03454>.
License: GPL (>= 3)
Language: en-US
URL: https://github.com/NSAPH-Software/GPCERF
BugReports: https://github.com/NSAPH-Software/GPCERF/issues
Copyright: Harvard University
Imports:
    parallel,
    xgboost,
    stats,
    MASS,
    spatstat.geom,
    logger,
    Rcpp,
    RcppArmadillo,
    ggplot2,
    cowplot,
    rlang,
    Rfast,
    SuperLearner,
    wCorr
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Depends: 
    R (>= 3.5.0)
Suggests: 
    rmarkdown,
    knitr,
    testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
LinkingTo: 
    RcppArmadillo,
    Rcpp