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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| 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 |