Block matrix approximation via entropy loss function

descriptionPublicationkeyboard_double_arrow_right Article 02 Nov 2020Publisher:Institute of Mathematics, Czech Academy of SciencesJournal:Applications of Mathematics, volume 65, pages 829-844

Authors: Janiszewska, Malwina; Markiewicz, Augustyn; Mokrzycka, Monika;

doi: 10.21136/am.2020.0023-20

Block matrix approximation via entropy loss function

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Abstract

The covariance matrix is one of the most important elements of probability calculation, it is a symmetric, positive-definite matrix. The question of how to approximate well has been raised many times. A solution to this problem is answered in this article. Symmetric, positive-definite matrices can be approximated by symmetric block partitioned matrices with structured off-diagonal blocks.

Related Organizations

Polish Academy of Learning
Poland

Keywords

covariance matrix, entropy loss function, Measures of association (correlation, canonical correlation, etc.), block covariance structure, Estimation in multivariate analysis, Special matrices, approximation

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