An Alternative Prior for Estimation in High-Dimensional Settings

IF 2.5 2区心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Structural Equation Modeling: A Multidisciplinary Journal Pub Date : 2024-06-25 DOI:10.1080/10705511.2023.2281279

Michael Nagel, Lukas Fischer, Tim Pawlowski, Augustin Kelava

引用次数: 0

Abstract

Bayesian estimations of complex regression models with high-dimensional parameter spaces require advanced priors, capable of addressing both sparsity and multicollinearity in the data. The Dirichle...

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高维环境下的另一种估计先验

对具有高维参数空间的复杂回归模型进行贝叶斯估计需要先进的先验，以解决数据的稀疏性和多重共线性问题。Dirichle...

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来源期刊

Structural Equation Modeling: A Multidisciplinary Journal 数学-数学跨学科应用

CiteScore

8.70

自引率

11.70%

发文量

审稿时长

>12 weeks

期刊介绍： Structural Equation Modeling: A Multidisciplinary Journal publishes refereed scholarly work from all academic disciplines interested in structural equation modeling. These disciplines include, but are not limited to, psychology, medicine, sociology, education, political science, economics, management, and business/marketing. Theoretical articles address new developments; applied articles deal with innovative structural equation modeling applications; the Teacher’s Corner provides instructional modules on aspects of structural equation modeling; book and software reviews examine new modeling information and techniques; and advertising alerts readers to new products. Comments on technical or substantive issues addressed in articles or reviews published in the journal are encouraged; comments are reviewed, and authors of the original works are invited to respond.