Add to ORKGThe paper concerns the strong uniform consistency and the asymptotic distribution of the kernel density estimator of random objects on a Riemannian manifolds, proposed by Pelletier (2005)
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
Nonparametric kernel estimation of density is widely used, how-ever, many of the pointwise and globa...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
The estimation of the underlying probability density of n i.i.d. random objects on a compact Riemann...
In this paper, we consider a k-nearest neighbor kernel type estimator when the random variables belo...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
AbstractThis paper develops the theory of density estimation on the Stiefel manifoldVk,m, whereVk,mi...
International audienceMain techniques of probability density estimation on Riemannian manifolds are ...
We consider practical density estimation from large data sets sampled on manifolds embedded in Eucli...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
AbstractThe Grassmann manifold Gk,m−k consists of k-dimensional hyperplanes in Rm and is equivalent ...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
Nonparametric kernel estimation of density is widely used, how-ever, many of the pointwise and globa...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
The estimation of the underlying probability density of n i.i.d. random objects on a compact Riemann...
In this paper, we consider a k-nearest neighbor kernel type estimator when the random variables belo...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
In this paper, we consider kernel type estimator with variable bandwidth when the random variables b...
AbstractThis paper develops the theory of density estimation on the Stiefel manifoldVk,m, whereVk,mi...
International audienceMain techniques of probability density estimation on Riemannian manifolds are ...
We consider practical density estimation from large data sets sampled on manifolds embedded in Eucli...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
AbstractThe Grassmann manifold Gk,m−k consists of k-dimensional hyperplanes in Rm and is equivalent ...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
Nonparametric kernel estimation of density is widely used, how-ever, many of the pointwise and globa...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...