Journal of the
Korean Mathematical Society
JKMS
ISSN(Print) 0304-9914
ISSN(Online) 2234-3008
Article
HOME
ALL ARTICLES
View
ALL ARTICLES
View
J. Korean Math. Soc. 2007; 44(4): 835-844
Printed July 1, 2007
Copyright © The Korean Mathematical Society.
LIL for kernel estimator of error distribution in regression model
Si-Li Niu
Tongji University
This paper considers the problem of estimating the error distribution function in nonparametric regression models. Sufficient conditions are given under which the kernel estimator of the error distribution function based on nonparametric residuals satisfies the law of iterated logarithm.
Keywords: law of iterated logarithm, kernel estimation, nonparametric residuals, empirical process
MSC numbers: Primary 62G07; Secondary 62F12
Article Tools
Stats or Metrics
Share this article on :
Related articles in JKMS
-
Weak convergence for stationary bootstrap empirical processes of associated sequences
2021; 58(1): 237-264
-
On almost sure representations for long memory sequences
1998; 35(3): 741-753
-
Small ball and large deviation probabilities estimates for Gaussian processes with stationary increments
1999; 36(3): 509-525
-
A law of the iterated logarithm for $l^p$-valued Gaussian random fields
2007; 44(6): 1441-1451
© 2022. The Korean Mathematical Society. Powered by INFOrang Co., Ltd