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A new strategy for finite-sample valid prediction of future insurance claims in the regression setting

arXiv 2601.21153 ↗First posted 29 Jan 2026stat.AP cs.LGcited by 0

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Abstract (arXiv)

The extant insurance literature demonstrates a paucity of finite-sample valid prediction intervals of future insurance claims in the regression setting. To address this challenge, this article proposes a new strategy that converts a predictive method in the unsupervised iid (independent identically distributed) setting to a predictive method in the regression setting. In particular, it enables an actuary to obtain infinitely many finite-sample valid prediction intervals in the regression setting.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 32 references that are in the map. First posted on arXiv 29 Jan 2026.

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5 of 32 references.

References · 5

  1. 2016Distribution-Free Predictive Inference For Regressioncited by 668
  2. 2020Methods to Compute Prediction Intervals: A Review and New Resultscited by 9
  3. 2017On overfitting and post-selection uncertainty assessmentscited by 6
  4. 2025Conformal prediction of future insurance claims in the regression problemcited by 2
  5. 2025On some practical challenges of conformal predictioncited by 1

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