Large and moderate deviation principles for nonparametric recursive kernel distribution estimators defined by stochastic approximation method
In this paper we prove large and moderate deviations principles for the recursive kernel estimators of a distribution function defined by the stochastic approximation algorithm. We show that the estimator constructed using the stepsize which minimize the Mean Integrated Squared Error (MISE) of the c...
Main Author: | |
---|---|
Format: | Article |
Language: | English |
Published: |
AGH Univeristy of Science and Technology Press
2019-01-01
|
Series: | Opuscula Mathematica |
Subjects: | |
Online Access: | https://www.opuscula.agh.edu.pl/vol39/5/art/opuscula_math_3941.pdf |