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>.

Package details

AuthorNaeem Khoshnevis [aut] (<https://orcid.org/0000-0003-4315-1426>, HUIT), Boyu Ren [aut, cre] (<https://orcid.org/0000-0002-5300-1184>, McLean Hospital), Tanujit Dey [ctb] (<https://orcid.org/0000-0001-5559-211X>, HMS), Danielle Braun [aut] (<https://orcid.org/0000-0002-5177-8598>, HSPH)
MaintainerBoyu Ren <bren@mgb.org>
LicenseGPL (>= 3)
Version0.2.4
URL https://github.com/NSAPH-Software/GPCERF
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("GPCERF")

Try the GPCERF package in your browser

Any scripts or data that you put into this service are public.

GPCERF documentation built on June 22, 2024, 11:30 a.m.