A diagonally weighted matrix norm between two covariance matrices

Carte non disponible

Date(s) - 25/03/2019
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories

The square of the Frobenius norm of a matrix $A$ is defined as the sum of squares of all the elements of $A$. An important application of the norm in statistics is when $A$ is the difference between a target (estimated or given) covariance matrix and a parameterized covariance matrix, whose parameters are chosen to minimize the Frobenius norm. In this article, we investigate weighting the Frobenius norm by putting more weight on the diagonal elements of $A$, with an application to spatial statistics. We find the spatial random effects (SRE) model that is closest, according to the the weighted Frobenius norm between covariance matrices, to a particular stationary Mat\’ern covariance model.


Posts created 14

Articles similaires

Commencez à saisir votre recherche ci-dessus et pressez Entrée pour rechercher. ESC pour annuler.

Retour en haut
Secured By miniOrange