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Updated: Jan 13, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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用于纵向和层次数据建模的创新统计方法:GMEXGBoost方法

Fariba Asadi1,2, Reza Homayounfar3,4, Yaser Mehrali5

  • 1Ferdows Faculty of Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran.

BMC medical research methodology
|January 7, 2026
PubMed
概括

一个名为GMEXGBoost的新算法通过结合通用混合效应模型和XGBoost.com来改进复杂医疗数据的分析. 它为具有强相关性的层次和纵向数据集提供了卓越的稳定性和准确性.

关键词:
提升了树的树.一般化的线性混合模型.纵向和层次的数据数据.

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