Distribution-Free Predictive Inference for Regression

We develop a general framework for distribution-free predictive inference in regression, using conformal inference. The proposed methodology allows for the construction of a prediction band for the response variable using any estimator of the regression function. The resulting prediction band preser...

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Bibliographic Details
Published in:	Journal of the American Statistical Association Vol. 113; no. 523; pp. 1094 - 1111
Main Authors:	Lei, Jing, G'Sell, Max, Rinaldo, Alessandro, Tibshirani, Ryan J., Wasserman, Larry
Format:	Journal Article
Language:	English
Published:	Alexandria Taylor & Francis 03.07.2018 Taylor & Francis Group,LLC Taylor & Francis Ltd
Subjects:	Computational efficiency computer software Computing time Distribution-free Empirical analysis equations heteroskedasticity Inference Intervals Model misspecification prediction Prediction band Predictions Property Regression Regression analysis Reproducibility Statistical analysis Statistical methods Statistics Theory and Methods Variable importance Variants
ISSN:	0162-1459, 1537-274X, 1537-274X
Online Access:	Get full text
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