Estimation of partially linear single-index spatial autoregressive model

被引：28

作者：

Cheng, Suli ^{[1
]}

Chen, Jianbao ^{[1
]}

机构：

[1] Fujian Normal Univ, Coll Math & Informat, Fuzhou 350117, Peoples R China

来源：

STATISTICAL PAPERS | 2021年 / 62卷 / 01期

基金：

中国国家社会科学基金; 中国国家自然科学基金;

关键词：

Partially linear single-index spatial autoregressive model; Profile maximum likelihood estimation; Consistency; Asymptotic normality; Monte Carlo simulation; VARIABLE SELECTION; STATISTICAL-INFERENCE; REGRESSION;

D O I：

10.1007/s00362-019-01105-y

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we first present partially linear single-index spatial autoregressive model and propose its profile maximum likelihood estimators (PMLE). Subsequently, consistency and asymptotic normality of the estimators for parameters and unknown link function are derived under some regular conditions. Thirdly, Monte Carlo simulations are used to investigate the performances of these estimators in finite sample cases. Finally, the proposed method is illustrated with the real data set of Boston Housing Price.

引用

页码：495 / 531

页数：37

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