29 citations · 71 across the 7 of their papers we have counts for
8 papers
Recursive density estimators based on Robbins-Monro's scheme and using Bernstein polynomials
Yousri SLAOUI, Asma JMAEI
In this paper, we consider the alleviation of the boundary problem when the probability density function has bounded support. We apply Robbins-Monro's algorithm and Bernstein polyn…
Optimal bandwidth selection for semi-recursive kernel regression estimators
Yousri Slaoui
In this paper we propose an automatic selection of the bandwidth of the semi-recursive kernel estimators of a regression function defined by the stochastic approximation algorithm.…
Bandwidth selection in deconvolution kernel distribution estimators defined by stochastic approximation method with Laplace errors
Yousri Slaoui
In this paper we consider the kernel estimators of a distribution function defined by the stochastic approximation algorithm when the observation are contamined by measurement erro…
Recursive kernel density estimators under missing data
Yousri Slaoui
In this paper we propose an automatic bandwidth selection of the recursive kernel density estimators with missing data in the context of global and local density estimation. We sho…
Large and moderate deviation principles for averaged stochastic approximation method for the estimation of a regression function
Yousri Slaoui
In this paper we prove large deviations principles for the averaged stochastic approximation method for the estimation of a regression function introduced by A. Mokkadem et al. [Re…
Large and moderate deviation principles for recursive kernel density estimators defined by stochastic approximation method
Yousri Slaoui
In this paper we prove large and moderate deviations principles for the recursive kernel estimators of a probability density function defined by the stochastic approximation algori…