Efficient Statistical Inference for Partially Nonlinear Errors-in-Variables Models

被引：3
|
作者：
Feng, San Ying [1 ]
Li, Gao Rong [1 ]
Zhang, Jun Hua [2 ]
机构：
[1] Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
[2] Beijing Informat Sci & Technol Univ, Coll Mech Engn, Beijing 100192, Peoples R China
来源：
ACTA MATHEMATICA SINICA-ENGLISH SERIES | 2014年 / 30卷 / 09期
基金：
北京市自然科学基金; 中国国家自然科学基金;
关键词：
Partially nonlinear errors-in-variables model; measurement error; ordinary smooth; profile nonlinear least squares; asymptotic property; LIKELIHOOD; REGRESSION;
D O I：
10.1007/s10114-014-1358-x
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we consider the partially nonlinear errors-in-variables models when the nonparametric component is measured with additive error. The profile nonlinear least squares estimator of unknown parameter and the estimator of nonparametric component are constructed, and their asymptotic properties are derived under general assumptions. Finite sample performances of the proposed statistical inference procedures are illustrated by Monte Carlo simulation studies.
引用
收藏
页码：1606 / 1620
页数：15
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