AbstractThe Fréchet distance between two multivariate normal distributions having means μX, μY and covariance matrices ΣX, ΣY is shown to be given by d2 = |μX − μY|2 + tr(ΣX + ΣY − 2(ΣXΣY)12). The quantity d0 given by d02 = tr(ΣX + ΣY − 2(ΣXΣY)12) is a natural metric on the space of real covariance matrices of given order
We show how the Riemannian distance on n++, the cone of n×n real symmetric or complex Hermitian po...
I consider the problem of estimating the Mahalanobis distance between multivariate normal population...
The distance covariance of two random vectors is a measure of their dependence. The empirical dista...
The Fréchet distance between two multivariate normal distributions having means [mu]X, [mu]Y and cov...
AbstractThe Fréchet distance between two multivariate normal distributions having means μX, μY and c...
AbstractThis paper shows an embedding of the manifold of multivariate normal densities with informat...
The construction of a distance function between probability distributions is of importance in mathem...
AbstractThe construction of a distance function between probability distributions is of importance i...
Este trabajo aborda el problema de comparar modelos lineales normales desde una perspectiva geométri...
AbstractWe determine Riemannian distances between a large class of multivariate probability densitie...
AbstractFor two p-dimensional random vectors X and Y with dispersion matrices Σ11 and Σ22, respectiv...
where a and b are twomultivariate observations, Σ− is the inverse of the variance-covariance matrix...
In this paper we study the main properties of a distance introduced by C.M. Cuadras (1974). This dis...
A framework is developed for inference concerning the covariance operator of a functional random pr...
It is a well-known fact that if the random vector W converges in distribution to a multivariate norm...
We show how the Riemannian distance on n++, the cone of n×n real symmetric or complex Hermitian po...
I consider the problem of estimating the Mahalanobis distance between multivariate normal population...
The distance covariance of two random vectors is a measure of their dependence. The empirical dista...
The Fréchet distance between two multivariate normal distributions having means [mu]X, [mu]Y and cov...
AbstractThe Fréchet distance between two multivariate normal distributions having means μX, μY and c...
AbstractThis paper shows an embedding of the manifold of multivariate normal densities with informat...
The construction of a distance function between probability distributions is of importance in mathem...
AbstractThe construction of a distance function between probability distributions is of importance i...
Este trabajo aborda el problema de comparar modelos lineales normales desde una perspectiva geométri...
AbstractWe determine Riemannian distances between a large class of multivariate probability densitie...
AbstractFor two p-dimensional random vectors X and Y with dispersion matrices Σ11 and Σ22, respectiv...
where a and b are twomultivariate observations, Σ− is the inverse of the variance-covariance matrix...
In this paper we study the main properties of a distance introduced by C.M. Cuadras (1974). This dis...
A framework is developed for inference concerning the covariance operator of a functional random pr...
It is a well-known fact that if the random vector W converges in distribution to a multivariate norm...
We show how the Riemannian distance on n++, the cone of n×n real symmetric or complex Hermitian po...
I consider the problem of estimating the Mahalanobis distance between multivariate normal population...
The distance covariance of two random vectors is a measure of their dependence. The empirical dista...
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