贝叶斯结构方程建模在建筑和拆除废物管理研究中的应用:规划行为扩展理论的开发
Nur Anisah Mohamed1, Ayed R A Alanzi2, Azlinna Noor Azizan3
1Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia.
PloS one
|January 23, 2024
概括
与ML和PLS相比,贝叶斯估计器为建筑和拆除废物管理 (C&DWM) 提供了优越的结构方程建模 (SEM),提供了更好的数据匹配和准确性. 这对于有效的废物管理策略至关重要.
科学领域:
- 环境科学与环境管理
- 土木工程和建筑工程.
- 统计建模 统计建模
背景情况:
- 有效的建筑和拆除废物管理 (C&DWM) 取决于构成者的态度和行动.
- 在C&DWM建模中选择最佳统计估计器的深度分析经常被忽视.
- 计划行为扩展理论 (扩展TPB) 为理解C&DWM行为提供了一个框架.
研究的目的:
- 在C&DWM中比较不同结构方程建模 (SEM) 估计器的性能.
- 根据扩展TPB.确定最适合用于基于扩展TPB.模拟C&DWM的估计器.
- 评估贝叶斯式,ML和PLS估计器的合适度和预测准确度.
主要方法:
- 结构方程建模 (SEM) 使用计划行为的扩展理论 (扩展TPB) 模型.
- 这项研究比较了三个估计器:最大概率 (ML),部分最小平方 (PLS) 和贝叶斯式.
- 模型性能使用R平方,RMSE,MPE和MSE进行评估,以及变量关系的意义.
主要成果:
- 贝叶斯估计器产生了最高的R平方 (85.8%),具有五个显著变量关系.
- ML估计器的结果是78.2%的R平方,有四个显著关系.
- PLS估计器显示了最低的R平方 (73.4%),有三个显著关系;贝叶斯还具有较低的错误指数 (RMSE,MPE,MSE).
结论:
- 与ML和PLS相比,贝叶斯估计器在C&DWM建模中表现出优越的合适性和预测准确性.
- 选择SEM估计器对观察到的变量与模型结果之间的关系产生重大影响.
- 研究人员必须仔细选择用于C&DWM分析的SEM估计器,以确保准确的建模和可靠的见解.
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