International audienceThis paper deals with non-parametric density estimation for spatial data. We study the asymptotic properties of a new recursive version of the Parzen–Rozenblatt estimator. The mean square error and an almost sure convergence result with rate of such estimator are derived
Non-parametric density estimation is the problem of approximating the values of a probability densit...
We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorizat...
Abstract. Non-parametric estimation of a density function is used as a vehicle to illustrate the sig...
International audienceThis paper deals with non-parametric density estimation for spatial data. We s...
AbstractThis paper deals with non-parametric density estimation for spatial data. We study the asymp...
In this thesis, we are interested in recursive methods that allow to update sequentially estimates i...
International audienceA non-parametric level set estimator of the density of a stationary d-dimensi...
AbstractA general nonparametric density estimation problem is considered in which the data is genera...
A novel non-parametric density estimator is developed based on geometric principles. A penalised cen...
Many directional data such as wind directions can be collected extremely easily so that experiments ...
We propose a nonparametric method for density estimation over (possibly complicated) spatial domains...
International audienceIn this paper, we propose a nonparametric method to estimate the spatial densi...
International audienceHall and Marron (1987) introduced kernel estimators of integrals of various sq...
Non-parametric density estimation is the problem of approximating the values of a probability densit...
We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorizat...
Abstract. Non-parametric estimation of a density function is used as a vehicle to illustrate the sig...
International audienceThis paper deals with non-parametric density estimation for spatial data. We s...
AbstractThis paper deals with non-parametric density estimation for spatial data. We study the asymp...
In this thesis, we are interested in recursive methods that allow to update sequentially estimates i...
International audienceA non-parametric level set estimator of the density of a stationary d-dimensi...
AbstractA general nonparametric density estimation problem is considered in which the data is genera...
A novel non-parametric density estimator is developed based on geometric principles. A penalised cen...
Many directional data such as wind directions can be collected extremely easily so that experiments ...
We propose a nonparametric method for density estimation over (possibly complicated) spatial domains...
International audienceIn this paper, we propose a nonparametric method to estimate the spatial densi...
International audienceHall and Marron (1987) introduced kernel estimators of integrals of various sq...
Non-parametric density estimation is the problem of approximating the values of a probability densit...
We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorizat...
Abstract. Non-parametric estimation of a density function is used as a vehicle to illustrate the sig...
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