International audienceThis paper is concerned with estimating the density mode for random field by kernel method under some α-mixing condition. The almost sure uniform convergence of the density estimator is proved. The rate of almost sure uniform convergence of the density gradient estimator is given under mild conditions. The unknown density is supposed unimodal and its mode is estimated by a kernel estimate. The strong consistency of the mode estimate is investigated and the rate of convergence is given. An optimal bandwidth selection procedure is proposed and a simulation study is used to obtain empirical results
Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimen...
The problem of the probability density estimation by using n size sample of stationary process is c...
The problem of the probability density estimation by using n size sample of stationary process is co...
International audienceWe are concerned with estimating the mode of a density of a spatial process by...
Four nonparametric estimates of the mode of a density function are investigated. Two mode estimates ...
In this paper, we establish a new proof of uniform consistency of kernel estimator of density functi...
A data-driven bandwidth choice for a kernel density estimator called critical bandwidth is investiga...
International audienceIn this paper, we propose a nonparametric method to estimate the spatial densi...
© 2018 Hanyuan Hang, Ingo Steinwart, Yunlong Feng and Johan A.K. Suykens. We study the density estim...
Let X be an -valued random variable with unknown density f. Let X1,...,Xn be i.i.d. random variables...
28 pagesIn this work, we establish the asymptotic normality of the deconvolution kernel density esti...
Various consistency proofs for the kernel density estimator have been developed over the last few d...
Based on a random sample of size n from an unknown density f on the real line, several data-driven m...
International audienceThis work studies the estimation of spectral density for random field (two-dim...
Asymptotic properties of a kernel density estimator using a random bandwidth are difficult to establ...
Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimen...
The problem of the probability density estimation by using n size sample of stationary process is c...
The problem of the probability density estimation by using n size sample of stationary process is co...
International audienceWe are concerned with estimating the mode of a density of a spatial process by...
Four nonparametric estimates of the mode of a density function are investigated. Two mode estimates ...
In this paper, we establish a new proof of uniform consistency of kernel estimator of density functi...
A data-driven bandwidth choice for a kernel density estimator called critical bandwidth is investiga...
International audienceIn this paper, we propose a nonparametric method to estimate the spatial densi...
© 2018 Hanyuan Hang, Ingo Steinwart, Yunlong Feng and Johan A.K. Suykens. We study the density estim...
Let X be an -valued random variable with unknown density f. Let X1,...,Xn be i.i.d. random variables...
28 pagesIn this work, we establish the asymptotic normality of the deconvolution kernel density esti...
Various consistency proofs for the kernel density estimator have been developed over the last few d...
Based on a random sample of size n from an unknown density f on the real line, several data-driven m...
International audienceThis work studies the estimation of spectral density for random field (two-dim...
Asymptotic properties of a kernel density estimator using a random bandwidth are difficult to establ...
Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimen...
The problem of the probability density estimation by using n size sample of stationary process is c...
The problem of the probability density estimation by using n size sample of stationary process is co...