Local linear least squares kernel regression for linear and circular predictors

Xu Qin; Jiang She Zhang; Xiao Dong Yan

doi:10.1080/03610926.2010.539751

Local linear least squares kernel regression for linear and circular predictors

Xu Qin
, Jiang She Zhang
, Xiao Dong Yan

数学与统计学院

Xi'an Jiaotong University
CAS - Institute of Atmospheric Physics

科研成果: 期刊稿件 › 文章 › 同行评审

7 引用（Scopus）

摘要

We extend nonparametric regression models with local linear least squares fitting using kernel weights to the case of linear and circular predictors. We derive the asymptotic properties of the conditional bias and variance of bivariate local linear least squares kernel estimators. A small simulation study and a real experiment are given.

源语言	英语
页（从-至）	3812-3823
页数	12
期刊	Communications in Statistics - Theory and Methods
卷	40
期	21
DOI	https://doi.org/10.1080/03610926.2010.539751
出版状态	已出版 - 1月 2011

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@article{cb55eb066d51433c81a4a12408e564bb,

title = "Local linear least squares kernel regression for linear and circular predictors",

abstract = "We extend nonparametric regression models with local linear least squares fitting using kernel weights to the case of linear and circular predictors. We derive the asymptotic properties of the conditional bias and variance of bivariate local linear least squares kernel estimators. A small simulation study and a real experiment are given.",

keywords = "Circular variable, Kernel, Least squares fitting, Nonparametric regression",

author = "Xu Qin and Zhang, \{Jiang She\} and Yan, \{Xiao Dong\}",

year = "2011",

month = jan,

doi = "10.1080/03610926.2010.539751",

language = "英语",

volume = "40",

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journal = "Communications in Statistics - Theory and Methods",

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TY - JOUR

T1 - Local linear least squares kernel regression for linear and circular predictors

AU - Qin, Xu

AU - Zhang, Jiang She

AU - Yan, Xiao Dong

PY - 2011/1

Y1 - 2011/1

N2 - We extend nonparametric regression models with local linear least squares fitting using kernel weights to the case of linear and circular predictors. We derive the asymptotic properties of the conditional bias and variance of bivariate local linear least squares kernel estimators. A small simulation study and a real experiment are given.

AB - We extend nonparametric regression models with local linear least squares fitting using kernel weights to the case of linear and circular predictors. We derive the asymptotic properties of the conditional bias and variance of bivariate local linear least squares kernel estimators. A small simulation study and a real experiment are given.

KW - Circular variable

KW - Kernel

KW - Least squares fitting

KW - Nonparametric regression

UR - https://www.scopus.com/pages/publications/80053272950

U2 - 10.1080/03610926.2010.539751

DO - 10.1080/03610926.2010.539751

M3 - 文章

AN - SCOPUS:80053272950

SN - 0361-0926

VL - 40

SP - 3812

EP - 3823

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 21

ER -

Local linear least squares kernel regression for linear and circular predictors

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