Asymptotic properties for the estimators in heteroscedastic semiparametric EV models with α-mixing errors

被引：2
|
作者：
Xi, Mengmei [1 ]
Wang, Rui [1 ]
Yu, Wei [1 ]
Shen, Yan [1 ]
Wang, Xuejun [1 ]
机构：
[1] Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China
来源：
STATISTICS | 2020年 / 54卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Semiparametric EV regression model; alpha-mixing errors; least squares estimator; strong consistency; PARTIAL LINEAR-MODELS; COMPLETE CONVERGENCE; RANDOM-VARIABLES; WEIGHTED SUMS; REGRESSION; NORMALITY; CONSISTENCY;
D O I：
10.1080/02331888.2020.1867857
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, the heteroscedastic semiparametric errors-in-variables (EV) model, yi = xi(i)beta + g(t(i)) + epsilon(i), x(i) = xi(i) + mu(i), 1 <= i <= n, is considered, where epsilon(i) = sigma(i)e(i), sigma(2)(i) = f (u(i)), beta is an unknown parameter to be estimated and g(center dot) and f (center dot) are unknown functions to be estimated. Under some suitable conditions, asymptotic properties for the estimators of beta, g(center dot) and f (center dot) are presented based on alpha-mixing random errors. In addition, finite sample behavior of the estimators is provided via simulations to verify the validity of the theoretical results.
引用
收藏
页码：1232 / 1254
页数：23
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