Add to ORKGThis article provides a central limit theorem for a consistent estimator of population eigenvalues with large multiplicities based on sample covariance matrices. The focus is on limited sample size situations, whereby the number of available observations is known and comparable in magnitude to the observation dimension. An exact expression as well as an empirical, asymptotically accurate, approximation of the limiting variance is derived. Simulations are performed that corroborate the theoretical claims. A specific application to wireless sensor networks is developed. I
International audienceThis paper studies the limiting behavior of a class of robust population covar...
Let A = 1/√np(XT X−pIn) where X is a p×n matrix, consisting of independent and identically distribut...
International audienceIn a spiked population model, the population covariance matrix has all its eig...
This article provides a central limit theorem for a consistent estimator of population eigenvalues w...
30 pp.International audienceThis article provides a central limit theorem for a consistent estimator...
This paper deals with the problem of estimating the covariance matrix of a series of independent mul...
We consider a spiked population model, proposed by Johnstone, whose population eigenvalues are all u...
We consider settings where the observations are drawn from a zero-mean multivariate (real or complex...
AbstractLimit theorems are given for the eigenvalues of a sample covariance matrix when the dimensio...
AbstractWe consider a spiked population model, proposed by Johnstone, in which all the population ei...
In a spiked population model, the population covariance matrix has all its eigenvalues equal to unit...
The first part of the dissertation investigates the application of the theory of large random matric...
Abstract. In the spiked population model introduced by Johnstone [10], the population covariance mat...
This article studies the limiting behavior of a class of robust population covariance matrix estimat...
Abstract: We consider a multivariate Gaussian observation model where the covariance matrix is diago...
International audienceThis paper studies the limiting behavior of a class of robust population covar...
Let A = 1/√np(XT X−pIn) where X is a p×n matrix, consisting of independent and identically distribut...
International audienceIn a spiked population model, the population covariance matrix has all its eig...
This article provides a central limit theorem for a consistent estimator of population eigenvalues w...
30 pp.International audienceThis article provides a central limit theorem for a consistent estimator...
This paper deals with the problem of estimating the covariance matrix of a series of independent mul...
We consider a spiked population model, proposed by Johnstone, whose population eigenvalues are all u...
We consider settings where the observations are drawn from a zero-mean multivariate (real or complex...
AbstractLimit theorems are given for the eigenvalues of a sample covariance matrix when the dimensio...
AbstractWe consider a spiked population model, proposed by Johnstone, in which all the population ei...
In a spiked population model, the population covariance matrix has all its eigenvalues equal to unit...
The first part of the dissertation investigates the application of the theory of large random matric...
Abstract. In the spiked population model introduced by Johnstone [10], the population covariance mat...
This article studies the limiting behavior of a class of robust population covariance matrix estimat...
Abstract: We consider a multivariate Gaussian observation model where the covariance matrix is diago...
International audienceThis paper studies the limiting behavior of a class of robust population covar...
Let A = 1/√np(XT X−pIn) where X is a p×n matrix, consisting of independent and identically distribut...
International audienceIn a spiked population model, the population covariance matrix has all its eig...