CONVERGENCE OF NON-LINEAR FUNCTIONALS OF SMOOTHED EMPIRICAL PROCESSES AND KERNEL DENSITY ESTIMATES
Authors:
Corinne Berzin a;
Jos
Le
n b;
Joaqu
n Ortega c
Le
n b;
Joaqu
n Ortega c
| Affiliations: | a Universit Pierre Mend s-France Grenoble France Corinne.Berzin@upmf-grenoble.fr. |
| b Universidad Central de Venezuela Caracas Venezuela jleon@euler.ciens.ucv.ve. | |
c Instituto Venezolano de Investigaciones Cient ficas and U.C.V. Caracas Venezuela. |
DOI:
10.1080/02331880290015440
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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Abstract
We consider regularizations by convolution of the empirical process and study the asymptotic behaviour of non-linear functionals of this process. Using a result for the same type of non-linear functionals of the Brownian bridge, shown in a previous paper [4], and a strong approximation theorem, we prove several results for the p-deviation in estimation of the derivatives of the density. We also study the asymptotic behaviour of the number of crossings of the smoothed empirical process defined by Yukich [17] and of a modified version of the Kullback deviation.
|
| Keywords: Non-linear Functionals; Empirical Process; Kernel Density Estimation; Crossings; Kullback-Leibler Deviation; Regularization By Convolution |

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