约束条件下测量误差模型的统计推断
Statistical inference of measurement error models with constraints
王照良 1张旭阳1
作者信息
- 1. 河南理工大学数学与信息科学学院,河南焦作 454000
- 折叠
摘要
考虑具有测量误差的线性模型在参数分量具有精确的线性约束条件下的统计推理,提出了偏差校正的拉格朗日乘子检验统计量,得到了受约束的纠偏最小二乘估计量,并在一定的正则性条件下,证明了所得估计量渐近服从正态分布.最后通过数值模拟研究了所提方法的有限样本性质.
Abstract
In this paper,we consider statistical inference for a linear model with measurement error when exact linear restriction on the parametric component is assumed to hold.We proposed a bias-corrected Lagrange multiplier test statistic,and obtain the constrained bias-corrected least square estimator.Under certain regularity conditions,the asymptotic normality for the estimator are proved.Finally,the numerical simulations are conducted to illustrate the finite sample performance of the proposed methods.
关键词
测量误差/回归模型/最小二乘估计/精确约束/偏差校正Key words
measurement error/regression models/least square estimation/exact constraint/bias-corrected引用本文复制引用
基金项目
教育部人文社会科学研究项目(20YJC910010)
河南理工大学博士基金(B2020-37)
出版年
2024
NETL
NSTL
万方数据