A Note on the Connection Between Trek Rules and Separable Nonlinear Least Squares in Linear Structural Equation Models

We show that separable nonlinear least squares (SNLLS) estimation is applicable to all linear structural equation models (SEMs) that can be specified in RAM notation. SNLLS is an estimation technique that has successfully been applied to a wide range of models, for example neural networks and dynami...

Descripción completa

Detalles Bibliográficos
Autores principales: Ernst, Maximilian S., Peikert, Aaron, Brandmaier, Andreas M., Rosseel, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Theory and Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977899/
https://www.ncbi.nlm.nih.gov/pubmed/36566451
http://dx.doi.org/10.1007/s11336-022-09891-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977899/
https://www.ncbi.nlm.nih.gov/pubmed/36566451
http://dx.doi.org/10.1007/s11336-022-09891-5

Ejemplares similares