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Updated: Jun 5, 2025

An R-Based Landscape Validation of a Competing Risk Model
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实证预测间隔应用于短期死亡率预测和过度死亡

Ricarda Duerst1,2, Jonas Schöley3

  • 1Max Planck Institute for Demographic Research, Konrad-Zuse-Straße 1, 18057, Rostock, Germany. duerst@demogr.mpg.de.

Population health metrics
|December 11, 2024
PubMed
概括

过度死亡估计可能是不可靠的,因为预测错误. 新的经验预测间隔提供了一种更准确的方法来研究每周死亡率趋势和过度死亡的季节性变化.

关键词:
在 COVID-19 疫情中,对交叉验证进行验证.经验预测的间隔时间.过多的死亡人数坚固性 坚固性

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