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")