Conformal Inference R Project
Maintained by Ryan Tibshirani
Based on work by Rina Barber, Emmanuel Candes, Max G'Sell, Jing Lei, Aaditya Ramdas, Alessandro Rinaldo, Ryan Tibshirani, Larry Wasserman
This repository contains R software tools for conformal inference. The current
emphasis is on conformal prediction in regression. We may eventually add tools
for density estimation and classification.
The folder "conformalInference" can be installed as an R package, providing
access to the software tools, and the file "conformalInference.pdf" contains
documentation.
The folder "lei2018" contains R code to reproduce all examples in the paper
Distribution-Free Predictive Inference for Regression
by Lei, G'Sell, Rinaldo, Tibshirani, Wasserman (2018). The folder
"tibshirani2019" contains R code to reproduce all examples in the paper
Conformal Prediction Under Covariate Shift
by Tibshirani, Barber, Candes, Ramdas (2019). This code all relies on the
"conformalInference" R package.
Relevant work (in reverse chronological order):
- Conformal Prediction Under Covariate Shift
by Ryan Tibshirani, Rina Barber, Emmanuel Candes, Aaditya Ramdas, Advances in
Neural Information Processing Systems, 2019.
- Distribution-Free Predictive Inference for Regression
by Jing Lei, Max G'Sell, Alessandro Rinaldo, Ryan Tibshirani, and Larry
Wasserman, Journal of the American Statistical Association, 113(523),
1094-1111, 2018.
- Distribution-Free Prediction Bands for Non-parametric Regression
by Jing Lei and Larry Wasserman, Journal of the Royal Statistical Society:
Series B, 76(1), 71-96, 2014.
- A Conformal Prediction Approach to Explore Functional Data
by Jing Lei, Alessandro Rinaldo, and Larry Wasserman, Annals of Mathematics
and Artificial Intelligence, 74(4), 29-43, 2013.
- Distribution Free Prediction Sets
by Jing Lei, James Robins, and Larry Wasserman, Journal of the American
Statistical Association, 108(501), 278-287, 2013.
- On-line Predictive Linear Regression by
Vladimir Vovk, Ilia Nouretdinov, and Alex Gammerman, Annals of Statistics,
37(3), 1566-1590, 2009.
- Algorithmic Learning in a Random World by Vladimir
Vovk, Alex Gammerman, and Glenn Shafer, Springer, 2005.
Install the R package
To install the conformalInference R package directly from github, run the
following in R:
library(devtools)
install_github(repo="ryantibs/conformal", subdir="conformalInference")