Geodesic
Strong consistency of the mode of multivariate recursive kernel density estimator under strong mixing hypothesis
Teoriâ slučajnyh processov, Tome 25 (2020) no. 2, pp. 61-73

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In this research paper, we define a kernel estimator of the mode based on the recursive kernel density estimator developed by [23]. In addition, we establish its almost sure convergence under strong mixing hypothesis. Finally, we corroborate these theoretical results through numerical simulations.
Keywords: Nonparametric estimation, Density estimation, Stochastic approximation, Strong mixing, Strong consistency.
Mots-clés : Mode 
@article{THSP_2020_25_2_a5,
     author = {Fatma Ben Khadher and Yousri Slaoui},
     title = {Strong consistency of the mode of multivariate recursive kernel density estimator under strong mixing hypothesis},
     journal = {Teori\^a slu\v{c}ajnyh processov},
     pages = {61--73},
     publisher = {mathdoc},
     volume = {25},
     number = {2},
     year = {2020},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/THSP_2020_25_2_a5/}
}
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Fatma Ben Khadher; Yousri Slaoui. Strong consistency of the mode of multivariate recursive kernel density estimator under strong mixing hypothesis. Teoriâ slučajnyh processov, Tome 25 (2020) no. 2, pp. 61-73. http://geodesic.mathdoc.fr/item/THSP_2020_25_2_a5/