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[期刊论文]

Statistical inference for semiparametric varying -coefficient spatial autoregressive models under restricted conditions

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作者:

Luo, Guowang (Luo, Guowang.) | Wu, Mixia (Wu, Mixia.) (学者:吴密霞)

收录:

EI Scopus SCIE

摘要:

This article considers statistical inference for restricted semiparametric varying-coefficient spatial autoregressive(SVCSAR) models. We propose a restricted estimation method for parametric and nonparametric components, and a Lagrange-multiplier-type test for testing hypotheses on the parametric component restrictions of SVCSAR models. Under mild conditions, we obtain the asymptotic normality for the resulting estimator of the parametric vector and the optimal convergence rate for that of nonparametric functions. Simulation studies are carried out to investigate the finite sample performance of the proposed method. The method is exemplified with Boston housing price data.

关键词:

Restricted conditions Semiparametric spatial autoregression Instrumental variable B-spline basis function

作者机构:

  • [ 1 ] [Luo, Guowang]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
  • [ 2 ] [Wu, Mixia]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China

通讯作者信息:

  • 吴密霞

    [Wu, Mixia]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China

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来源 :

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION

ISSN: 0361-0918

年份: 2019

期: 5

卷: 51

页码: 2268-2286

0 . 9 0 0

JCR@2022

ESI学科: MATHEMATICS;

ESI高被引阀值:54

被引次数:

WoS核心集被引频次: 4

SCOPUS被引频次: 3

近30日浏览量: 2

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