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arXiv · 1603.09141

Estimating multivariate latent-structure models

Stéphane Bonhomme·Koen Jochmans·Jean-Marc Robin
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Abstract

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 nonorthogonal 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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Stéphane Bonhomme, Koen Jochmans, Jean-Marc Robin. 2016-03-30. Estimating multivariate latent-structure models. https://doi.org/10.1214/15-aos1376

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