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Estimating Multivariate Latent-Structure Models

 

Notice

Type:   Article
 
Titre:   Estimating Multivariate Latent-Structure Models
 
Auteur(s):   Bonhomme, Stéphane - University of Chicago (Auteur)
Jochmans, Koen (1982-...) - Département d'économie (Auteur)
Robin, Jean-Marc (1961-...) - Département d'économie (Auteur)
 
In:   Annals of Statistics
 
Date de publication:   2016
 
Volume:   Forthcoming
 
ISSN:   00905364
 
Résumé:   [en] A constructive proof of identification of multilinear decompositions of multiway arrays is presented. It can be applied to show identification in a variety of multivariate latent structures. Examples are finite-mixture models and hidden Markov models. The key step to show identification is the joint diagonalization of a set of matrices in the same non-orthogonal basis. An estimator of the latent-structure model may then be based on a sample version of this joint-diagonalization problem. Algorithms are available for computation and we derive distribution theory. We further develop asymptotic theory for orthogonal-series estimators of component densities in mixture models and emission densities in hidden Markov models.
 
 

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Version de l'auteur 2016-bonhomme-jochmans-robin-estimating-multivariate-latent-structure-models.pdf 0,47 MB
 

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