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arxiv 1111.1418 v1 pith:D67RTAUF submitted 2011-11-06 math.ST cs.LGstat.TH

Efficient Nonparametric Conformal Prediction Regions

classification math.ST cs.LGstat.TH
keywords regionspredictionbandwidthconformaldistributionmethodnonparametricapproximations
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We investigate and extend the conformal prediction method due to Vovk,Gammerman and Shafer (2005) to construct nonparametric prediction regions. These regions have guaranteed distribution free, finite sample coverage, without any assumptions on the distribution or the bandwidth. Explicit convergence rates of the loss function are established for such regions under standard regularity conditions. Approximations for simplifying implementation and data driven bandwidth selection methods are also discussed. The theoretical properties of our method are demonstrated through simulations.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. On Optimal Data Splitting for Split Conformal Prediction

    math.ST 2026-06 unverdicted novelty 6.0

    Derives analytical characterizations of the length-optimal training-calibration split ratio for split conformal prediction in general settings and specific regression models.

  2. A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

    cs.LG 2021-07 unverdicted novelty 5.0

    Pith review generated a malformed one-line summary.

  3. Theoretical Foundations of Conformal Prediction

    math.ST 2024-11 unverdicted novelty 2.0

    The book curates and presents proofs of important existing results in conformal prediction in a unified pedagogical format with illustrations.