Estimation and testing for lattice conditional independence models on Euclidean Jordan algebras

DOI10.1214/aos/1024691088zbMath0932.62067OpenAlexW2003187299MaRDI QIDQ1807103

Erhard Neher, Hélène Massam

Publication date: 9 November 1999

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1024691088

zbMATH Keywords

symmetric conesEuclidean Jordan algebraWishart distributionscovariance selectionlattice conditional independence models

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Hypothesis testing in multivariate analysis (62H15) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Jordan algebras (algebras, triples and pairs) (17C99)

Related Items

Characterization of Wishart-Laplace distributions via Jordan algebra homomorphisms, A universal algebraic approach for conditional independence, Euclidean Jordan Algebras and Strongly Regular Graphs, Extremal rays and duals for cones of positive definite matrices with prescribed zeros, Estimation of normal covariance matrices parametrized by irreducible symmetric cones under Stein's loss, Convexity and differentiability properties of spectral functions and spectral mappings on Euclidean Jordan algebras, Lattice conditional independence models and Hibi ideals, Simulation of hyper-inverse Wishart distributions for non-decomposable graphs, Enriched conjugate and reference priors for the Wishart family on symmetric cones, Wishart-Laplace distributions associated with matrix quadratic forms, Unnamed Item, Conditional independence models for seemingly unrelated regressions with incomplete data, Inadmissibility of the maximum likelihood estimator of normal covariance matrices with the lattice conditional independence, Jordan algebras and dual affine connections on symmetric cones, Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models, Covariance selection and multivariate dependence

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