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Large and moderate deviation principles for recursive kernel density
  estimators defined by stochastic approximation method

Large and moderate deviation principles for recursive kernel density estimators defined by stochastic approximation method

27 January 2013
Y. Slaoui
ArXiv (abs)PDFHTML

Papers citing "Large and moderate deviation principles for recursive kernel density estimators defined by stochastic approximation method"

4 / 4 papers shown
Recursive density estimators based on Robbins-Monro's scheme and using
  Bernstein polynomials
Recursive density estimators based on Robbins-Monro's scheme and using Bernstein polynomials
Y. Slaoui
A. Jmaei
82
26
0
14 Apr 2019
Optimal bandwidth selection for semi-recursive kernel regression
  estimators
Optimal bandwidth selection for semi-recursive kernel regression estimators
Y. Slaoui
216
35
0
04 Jul 2016
Bandwidth selection in deconvolution kernel distribution estimators
  defined by stochastic approximation method with Laplace errors
Bandwidth selection in deconvolution kernel distribution estimators defined by stochastic approximation method with Laplace errors
Y. Slaoui
157
1
0
25 Jun 2016
Recursive kernel density estimators under missing data
Recursive kernel density estimators under missing data
Y. Slaoui
177
5
0
22 Jun 2016
1
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