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20152026
most citedOn multivariate associated kernels for smoothing general density functions

29 citations · 54 across the 6 of their papers we have counts for

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math.ST2026

Model-assisted estimation of the finite population mean via local linear regression with associated kernels

Sobom M. Somé, Idrissa Dimzouré

In this paper, we propose a general regression-assisted estimator of the population mean based on local regression with associated kernels, a broad class that encompasses both clas…

math.ST2025

An effective estimation of multivariate density functions using extended-beta kernels with Bayesian adaptive bandwidths

Sobom M. Somé, Célestin C. Kokonendji, Francial G. B. Libengué Dobélé-Kpoka

Multivariate kernel density estimations have received much spate of interest. In addition to conventional methods of (non-)classical associated-kernels for (un)bounded densities an…

math.ST2022★ 5 cited

Asymptotic properties of the normalized discrete associated-kernel estimator for probability mass function

Youssef Esstafa, Célestin C. Kokonendji, Sobom M. Somé

Discrete kernel smoothing is now gaining importance in nonparametric statistics. In this paper, we investigate some asymptotic properties of the normalized discrete associated-kern…

math.ST2022★ 3 cited

Multiple combined gamma kernel estimations for nonnegative data with Bayesian adaptive bandwidths

Sobom M. Somé, Célestin C. Kokonendji, Smail Adjabi +2

A modified gamma kernel should not be automatically preferred to the standard gamma kernel, especially for univariate convex densities with a pole at the origin. In the multivariat…

math.ST2015★ 16 cited

Effects of associated kernels in nonparametric multiple regressions

Sobom M. Somé, Célestin C. Kokonendji

Associated kernels have been introduced to improve the classical continuous kernels for smoothing any functional on several kinds of supports such as bounded continuous and discret…

math.ST2015★ 29 cited

On multivariate associated kernels for smoothing general density functions

Célestin C. Kokonendji, Sobom M. Somé

Multivariate associated kernel estimators, which depend on both target point and bandwidth matrix, are appropriate for partially or totally bounded distributions and generalize the…