Multivariate Statistical Analysis: A Geometric Perspective

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dc.creatorTyurin, Yuri N.
dc.date2009-02-03
dc.date.accessioned2026-07-07T12:37:15Z
dc.date.available2026-07-07T12:37:15Z
dc.descriptionA new, coordinate-free (geometric) approach to multivariate statistical analysis. General multivariate linear models and linear hypotheses are defined in geometric form. A method of constructing statistical criteria is defined for linear hypotheses. As a result, multivariate statistical analysis is developed in full analogy to classical statistical analysis. This approach is based on tensor products and modules over the ring of square matrices, supplied with an inner product.
dc.description25 pages
dc.identifierhttps://arxiv.org/abs/0902.0408
dc.identifierhttp://arxiv.org/abs/0902.0408
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/218373
dc.subjectStatistics Theory
dc.subject62H15, 62H12 (Primary) 62J05, 62J12 (Secondary)
dc.titleMultivariate Statistical Analysis: A Geometric Perspective
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