Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure

DOI10.1016/j.jmva.2015.05.019zbMath1328.62135arXiv1410.2118OpenAlexW2192555015MaRDI QIDQ900816

Fetsje Bijma, Beata Roś, Jan C. de Munck, Mathisca C. M. de Gunst

Publication date: 23 December 2015

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1410.2118

zbMATH Keywords

maximum likelihood estimationcovariance matrixKronecker product structureexistence and uniqueness of estimatormatrix normal model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Point estimation (62F10) Parametric inference under constraints (62F30) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (9)

A note on necessary and sufficient conditions of existence and uniqueness for the maximum likelihood estimator of a Kronecker-product variance-covariance matrix ⋮ Gaussian and robust Kronecker product covariance estimation: existence and uniqueness ⋮ An expectation-maximization algorithm for the matrix normal distribution with an application in remote sensing ⋮ Probabilistic partial least squares model: identifiability, estimation and application ⋮ Almost sure uniqueness of a global minimum without convexity ⋮ Maximum likelihood estimation for tensor normal models via castling transforms ⋮ Independent component analysis for tensor-valued data ⋮ A Penalized Likelihood Method for Classification With Matrix-Valued Predictors ⋮ Maximum Likelihood Estimation for Matrix Normal Models via Quiver Representations

Cites Work

• Models with a Kronecker product covariance structure: estimation and testing
• Transposable regularized covariance models with an application to missing data imputation
• The ubiquitous Kronecker product
• The likelihood ratio test for a separable covariance matrix
• Theoretical Statistics
• The mle algorithm for the matrix normal distribution
• On Estimation of Covariance Matrices With Kronecker Product Structure
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