Skip to Main content Skip to Navigation
Conference papers

Contributions to Bayesian Structural Equation Modeling

Abstract : Structural equation models (SEMs) are multivariate latent variable models used to model causality structures in data. A Bayesian estimation and validation of SEMs is proposed and identi ability of parameters is studied. The latter study shows that latent variables should be standardized in the nalysis to ensure identi fiability. This heuristics is in fact introduced to deal with complex identi ability constraints. To illustrate the point, identi ability constraints are calculated in a marketing application, in which posterior draws of the constraints are derived from the posterior conditional distributions of parameters.
Complete list of metadatas

Cited literature [6 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01125763
Contributor : Laboratoire Cedric <>
Submitted on : Sunday, March 22, 2020 - 7:34:35 PM
Last modification on : Thursday, March 26, 2020 - 1:18:53 AM

File

art_1929.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01125763, version 1

Collections

Citation

Séverine Demeyer, Nicolas Fischer, Gilbert Saporta. Contributions to Bayesian Structural Equation Modeling. COMPSTAT'2010, 19th International Conference on Computational Statistics, Paris, Aug 2010, Paris, France. pp.469-476. ⟨hal-01125763⟩

Share

Metrics

Record views

76

Files downloads

40