On completing a measurement model by symmetry
arXiv (Cornell University)(2021)
摘要
An appeal for symmetry is made to build established notions of specific representation and specific nonlinearity of measurement (often called model error) into a canonical linear regression model. Additive components are derived from the trivially complete model M = m. Factor analysis and equation error motivate corresponding notions of representation and nonlinearity in an errors-in-variables framework, with a novel interpretation of terms. It is suggested that a modern interpretation of correlation involves both linear and nonlinear association.
更多查看译文
关键词
measurement model,symmetry
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要