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Updated: Sep 14, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Published on: July 3, 2020

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为一般化估计方程进行调整的预测

Francis K C Hui1, Samuel Muller2, Alan H Welsh1

  • 1Research School of Finance, Actuarial Studies and Statistics, The Australian National University, Canberra, ACT 2601, Australia.

Biometrics
|July 24, 2025
PubMed
概括

本研究引入了一种改进的预测方法,用于使用通用估计方程 (GEE) 进行纵向数据分析. 调整后的GEE预测器通过利用交叉相关性来增强未来的预测,优于标准方法.

关键词:
与相关数据相关联的数据.战争 战争 战争纵向数据 纵向数据 纵向数据这是边际回归的边际回归.预测 预测 预测 预测工作相关性 工作相关性

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