A0802
Title: Statistical learning in nonparametric q-kernel q-density estimation
Authors: Oumaima Ben Mrad - CNRS and University of Poitiers (France) [presenting]
Yousri Slaoui - University of Poitiers (France)
Afif Masmoudi - University of Sfax (Tunisia)
Abstract: In the context of quantum calculus, the interest is in statistical learning of nonparametric kernel density estimation. Firstly, we propose two q-density estimations. The first one is based on a q-Uniform kernel and the second is based on a q-Gaussian kernel. Secondly, we focus on characteristics related to Jackson's q-integral and q-derivative and we investigate the asymptotic properties of the two proposed q-kernel q-density estimators. Moreover, we conduct a numerical study to show the efficiency and the feasibility of the two proposed estimators by considering various values of the $q$ parameters and various sample sizes.
