You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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.
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 Sets
by Jing Lei, James Robins, and Larry Wasserman, Journal of the American
Statistical Association, 108(501), 278-287, 2013.