Strong convergence in nonparametric estimation of regression functions

K. F. Cheng

doi:10.1007/BF01855429

Strong convergence in nonparametric estimation of regression functions

K. F. Cheng

研究成果: 雜誌貢獻 › 文章 › 同行評審

1 引文斯高帕斯（Scopus）

摘要

The nonparametric regression problem has the objective of estimating conditional expectation. Consider the model {Mathematical expression}, where the random variable Z has mean zero and is independent of X. The regression function R(x) is the conditional expectation of Y given X = x. For an estimator of the form {Mathematical expression}, we obtain the rate of strong uniform convergence {Mathematical expression}. Here X is a d-dimensional variable and C is a suitable subset of R^d.

原文	英語
頁（從 - 到）	177-187
頁數	11
期刊	Periodica Mathematica Hungarica
卷	14
發行號	2
DOIs	https://doi.org/10.1007/BF01855429
出版狀態	已發佈 - 6月 1983
對外發佈	是

ASJC Scopus subject areas

數學(全部)

存取文件

10.1007/BF01855429

其它文件與鏈接

Link to publication in Scopus

引用此

@article{009492c773a944c382a68d82512abb75,

title = "Strong convergence in nonparametric estimation of regression functions",

abstract = "The nonparametric regression problem has the objective of estimating conditional expectation. Consider the model {Mathematical expression}, where the random variable Z has mean zero and is independent of X. The regression function R(x) is the conditional expectation of Y given X = x. For an estimator of the form {Mathematical expression}, we obtain the rate of strong uniform convergence {Mathematical expression}. Here X is a d-dimensional variable and C is a suitable subset of Rd.",

keywords = "AMS (MOS) subject classifications (1970): Primary 62G05, Secondary 60F15, Nonparametric regression, strong convergence",

author = "Cheng, {K. F.}",

year = "1983",

month = jun,

doi = "10.1007/BF01855429",

language = "English",

volume = "14",

pages = "177--187",

journal = "Periodica Mathematica Hungarica",

issn = "0031-5303",

publisher = "Springer Netherlands",

number = "2",

}

TY - JOUR

T1 - Strong convergence in nonparametric estimation of regression functions

AU - Cheng, K. F.

PY - 1983/6

Y1 - 1983/6

N2 - The nonparametric regression problem has the objective of estimating conditional expectation. Consider the model {Mathematical expression}, where the random variable Z has mean zero and is independent of X. The regression function R(x) is the conditional expectation of Y given X = x. For an estimator of the form {Mathematical expression}, we obtain the rate of strong uniform convergence {Mathematical expression}. Here X is a d-dimensional variable and C is a suitable subset of Rd.

AB - The nonparametric regression problem has the objective of estimating conditional expectation. Consider the model {Mathematical expression}, where the random variable Z has mean zero and is independent of X. The regression function R(x) is the conditional expectation of Y given X = x. For an estimator of the form {Mathematical expression}, we obtain the rate of strong uniform convergence {Mathematical expression}. Here X is a d-dimensional variable and C is a suitable subset of Rd.

KW - AMS (MOS) subject classifications (1970): Primary 62G05, Secondary 60F15

KW - Nonparametric regression

KW - strong convergence

UR - http://www.scopus.com/inward/record.url?scp=34250150873&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34250150873&partnerID=8YFLogxK

U2 - 10.1007/BF01855429

DO - 10.1007/BF01855429

M3 - Article

AN - SCOPUS:34250150873

SN - 0031-5303

VL - 14

SP - 177

EP - 187

JO - Periodica Mathematica Hungarica

JF - Periodica Mathematica Hungarica

IS - 2

ER -

Strong convergence in nonparametric estimation of regression functions

摘要

ASJC Scopus subject areas

存取文件

其它文件與鏈接

指紋

引用此