提出新方法，实现保险索赔预测的精确区间估计。
A new strategy for finite-sample valid prediction of future insurance claims in the regression setting
- 将无监督独立同分布方法转化为回归设置下的预测策略。
- 可生成无限多个有限样本下有效的预测区间。
- 适合精算师在小样本下进行可靠的风险评估。
现有保险文献中，针对回归设置下未来保险索赔的有限样本有效预测区间研究不足。本文提出一种新策略，将无监督独立同分布（iid）设定下的预测方法转换为回归设定下的预测方法。该方法使精算师能够在回归设置下获得无限多个有限样本有效的预测区间，显著提升了小样本条件下预测的可靠性与准确性。
原文摘要 · Abstract (English)
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.
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