UNIVERSITY
OF WROCŁAW
 
Main Page
Contents
Online First
General Information
Instructions for authors


VOLUMES
45.2 45.1 44.2 44.1 43.2 43.1 42.2
42.1 41.2 41.1 40.2 40.1 39.2 39.1
38.2 38.1 37.2 37.1 36.2 36.1 35.2
35.1 34.2 34.1 33.2 33.1 32.2 32.1
31.2 31.1 30.2 30.1 29.2 29.1 28.2
28.1 27.2 27.1 26.2 26.1 25.2 25.1
24.2 24.1 23.2 23.1 22.2 22.1 21.2
21.1 20.2 20.1 19.2 19.1 18.2 18.1
17.2 17.1 16.2 16.1 15 14.2 14.1
13.2 13.1 12.2 12.1 11.2 11.1 10.2
10.1 9.2 9.1 8 7.2 7.1 6.2
6.1 5.2 5.1 4.2 4.1 3.2 3.1
2.2 2.1 1.2 1.1
 
 
WROCŁAW UNIVERSITY
OF SCIENCE AND
TECHNOLOGY

Contents of PMS, Vol. 45, Fasc. 2,
pages 191 - 209
DOI: 10.37190/0208-4147.00249
Published online 28.1.2026
 

On consistency of wavelet estimators in nonparametric regression models with widely orthant dependent samples

Y. Wang
Y.Wu
X.Wang

Abstract:

In this paper, we mainly investigate the nonparametric regression model based on widely orthant dependent samples. The weak consistency, strong consistency, complete consistency, and the rates of strong consistency and complete consistency for the wavelet estimator are established under some mild conditions, which generalize and improve the corresponding ones for other dependent cases. Some numerical simulations are presented to verify the validity of the theoretical results based on finite samples.

2010 AMS Mathematics Subject Classification: Primary 60F15; Secondary 62F12.

Keywords and phrases: nonparametric regression model, widely orthant dependent random variables, wavelet estimator, consistency, the rate of consistency.

Download:        Full text