Add to ORKGAbstract. The consistency and asymptotic normality of the spatial sign covariance matrix with unknown loc-ation are shown. Simulations illustrate the different asymptotic behavior when using the mean and the spatial median as location estimator
Correlated multivariate processes have a dependence structure which must be taken into account when ...
When a linear model is used to analyze spatially correlated data, but the form of the spatial correl...
Covariance parameter estimation of Gaussian processes is analyzed in an asymptotic frame-work. The s...
In this paper, we consider the asymptotic properties of the spatial sign autocovariance matrix for G...
Tallennetaan OA-artikkeli, kun julkaistu / KSIn this paper, we consider the asymptotic properties of...
The asymptotic efficiency of the spatial sign covariance matrix (SSCM) relative to affine equivarian...
Due to increased recording capability, functional data analysis has become an important research top...
The well-known spatial sign covariance matrix (SSCM) carries out a radial transform which moves all ...
There has been a growing interest in providing models for multivariate spatial processes. A majority...
Abstract. A new robust correlation estimator based on the spatial sign covariance matrix (SSCM) is p...
The Sign Covariance Matrix is an orthogonal equivariant estimator of multivariate scale. It is often...
AbstractCorrelated multivariate processes have a dependence structure which must be taken into accou...
The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is oft...
Publisher Copyright: This work is licensed under a Creative Commons Attribution 4.0 License. For mor...
The spatial median and spatial sign covariance matrix (SSCM) are popularly used robust alternatives ...
Correlated multivariate processes have a dependence structure which must be taken into account when ...
When a linear model is used to analyze spatially correlated data, but the form of the spatial correl...
Covariance parameter estimation of Gaussian processes is analyzed in an asymptotic frame-work. The s...
In this paper, we consider the asymptotic properties of the spatial sign autocovariance matrix for G...
Tallennetaan OA-artikkeli, kun julkaistu / KSIn this paper, we consider the asymptotic properties of...
The asymptotic efficiency of the spatial sign covariance matrix (SSCM) relative to affine equivarian...
Due to increased recording capability, functional data analysis has become an important research top...
The well-known spatial sign covariance matrix (SSCM) carries out a radial transform which moves all ...
There has been a growing interest in providing models for multivariate spatial processes. A majority...
Abstract. A new robust correlation estimator based on the spatial sign covariance matrix (SSCM) is p...
The Sign Covariance Matrix is an orthogonal equivariant estimator of multivariate scale. It is often...
AbstractCorrelated multivariate processes have a dependence structure which must be taken into accou...
The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is oft...
Publisher Copyright: This work is licensed under a Creative Commons Attribution 4.0 License. For mor...
The spatial median and spatial sign covariance matrix (SSCM) are popularly used robust alternatives ...
Correlated multivariate processes have a dependence structure which must be taken into account when ...
When a linear model is used to analyze spatially correlated data, but the form of the spatial correl...
Covariance parameter estimation of Gaussian processes is analyzed in an asymptotic frame-work. The s...