使用贝叶斯模型的最佳仪器选择 模型的平均值 隐含的仪器变量 两阶段最小平方估计器

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Updated: May 7, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

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Teague Henry1, Zachary Fisher2, Kenneth Bollen3

  • 1Psychology & Data Science, University of Virginia.

Structural equation modeling : a multidisciplinary journal
|December 30, 2024
PubMed
概括

一种新方法,即模型隐式仪表变量双阶段贝叶斯式模型平均值 (MIIV-2SBMA),改进了现有的潜在变量模型技术. 它提供了更强大的能力来检测有问题的和弱的工具,帮助统计分析.

关键词:
贝叶斯模型的平均值.经验贝叶斯g-前期的经验.模型隐含的工具变量结构方程建模 结构方程建模两个阶段的最小平方.

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