Least square estimation of non-linear structural models
- 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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| Author: | Reinhard OldenburgORCiDGND |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1107633 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/110763 |
| Parent Title (English): | Statistics, Optimization & Information Computing |
| Publisher: | International Academic Press |
| Place of publication: | Wan Chai |
| Type: | Article |
| Language: | English |
| Year of first Publication: | 2024 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2024/01/15 |
| Volume: | 12 |
| Issue: | 2 |
| First Page: | 281 |
| Last Page: | 297 |
| DOI: | https://doi.org/10.19139/soic-2310-5070-1868 |
| Institutes: | Mathematisch-Naturwissenschaftlich-Technische Fakultät |
| Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik | |
| Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik / Lehrstuhl für Didaktik der Mathematik | |
| Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik |
| Licence (German): |  CC-BY 3.0: Creative Commons - Namensnennung (mit Print on Demand) |
