Least square estimation of non-linear structural models

  • Reinhard Oldenburg Augsburg University, Germany
Keywords: Structural equation model, Simulation study, Nonlinear regression model, error estimation

Abstract

A new method for estimating a wide class of structural equation models (SEM) is proposed and evaluated. A weighted least squares approach is used that estimates parameters and latent variables. This new approach is flexible enough to handle non-linear and non-smooth models and allows us to model various constraints. The method includes various strategies to deal with the problem of choosing weights. The principle strengths and weaknesses of this approach are discussed, and simulation studies are performed to reveal the problems and potential of this approach.

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Published
2023-12-18
How to Cite
Oldenburg, R. (2023). Least square estimation of non-linear structural models. Statistics, Optimization & Information Computing, 12(2), 281-297. https://doi.org/10.19139/soic-2310-5070-1868
Section
Research Articles