Gaussian Markov triplets approached by block matrices

Multivariate normal distributions are described by a positive definite matrix and if their joint distribution is Gaussian as well then it can be represented by a block matrix. The aim of this note is to study Markov triplets by using the block matrix technique. A Markov triplet is characterized by t...

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Elmentve itt :
Bibliográfiai részletek
Szerzők: Ando Tsuyoshi
Petz Dénes
Dokumentumtípus: Cikk
Megjelent: Bolyai Institute, University of Szeged Szeged 2009
Sorozat:Acta scientiarum mathematicarum 75 No. 1-2
Kulcsszavak:Matematika
Tárgyszavak:
Online Access:http://acta.bibl.u-szeged.hu/16305
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520 3 |a Multivariate normal distributions are described by a positive definite matrix and if their joint distribution is Gaussian as well then it can be represented by a block matrix. The aim of this note is to study Markov triplets by using the block matrix technique. A Markov triplet is characterized by the form of its block covariance matrix and by the form of the inverse of this matrix. A strong subadditivity of entropy is proved for a triplet and equality corresponds to the Markov property. The results are applied to multivariate stationary homogeneous Gaussian Markov chains. 
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