Annals of Statistics
- Ann. Statist.
- Volume 39, Number 2 (2011), 865-886.
Global identifiability of linear structural equation models
Structural equation models are multivariate statistical models that are defined by specifying noisy functional relationships among random variables. We consider the classical case of linear relationships and additive Gaussian noise terms. We give a necessary and sufficient condition for global identifiability of the model in terms of a mixed graph encoding the linear structural equations and the correlation structure of the error terms. Global identifiability is understood to mean injectivity of the parametrization of the model and is fundamental in particular for applicability of standard statistical methodology.
Ann. Statist., Volume 39, Number 2 (2011), 865-886.
First available in Project Euclid: 9 March 2011
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Drton, Mathias; Foygel, Rina; Sullivant, Seth. Global identifiability of linear structural equation models. Ann. Statist. 39 (2011), no. 2, 865--886. doi:10.1214/10-AOS859. https://projecteuclid.org/euclid.aos/1299680957