Generalized Conformal Prediction

Vladimir Vovk, Alexander Gammerman and Glenn Shafer
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Vladimir Vovk: University of London, Royal Holloway
Alexander Gammerman: University of London, Royal Holloway
Glenn Shafer: Rutgers University

Chapter Chapter 11 in Algorithmic Learning in a Random World, 2022, pp 333-362 from Springer

Abstract: Abstract In the previous chapters we assumed that the data are generated from an exchangeable probability measure. In this chapter we generalize the method of conformal prediction to cover arbitrary statistical models that belong to the class of, as we call them, online compression models. Interesting online compression models include, e.g., partial exchangeability models, Gaussian models, and causal networks.

Keywords: Online compression model; Repetitive structure; One-off structure; Exchangeability model; Partial exchangeability model; Gaussian model; Gauss linear model; Multivariate Gaussian model (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-06649-8_11

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DOI: 10.1007/978-3-031-06649-8_11

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