Estimation and inference for varying coefficient partially nonlinear errors-in-variables models
Estimation and inference for varying coefficient partially nonlinear errors-in-variables models
复制标题
变系数部分非线性变量误差模型的估计和推断
DOI：
10.1080/03610918.2017.1332217
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Zhanshou Chen
中科院分区：
文献类型：
--
作者：
Yanting Xiao;Zhanshou Chen
本文研究了非参数部分具有测量误差的变系数部分非线性模型。本文提出了一种局部校正轮廓非线性最小二乘估计方法，并建立了估计量的渐近性质。此外，广义似然比（GLR）统计量的建议，以测试是否变化的系数是常数。得到了该统计量的渐近零分布，并采用基于残差的Bootstrap方法计算了该统计量的p值。一些模拟进行评估所提出的方法的性能。结果表明，估计和检验程序在有限样本下工作良好。
In this article, we study the varying coefficient partially nonlinear model with measurement errors in the nonparametric part. A local corrected profile nonlinear least-square estimation procedure is proposed and the asymptotic properties of the resulting estimators are established. Further, a generalized likelihood ratio (GLR) statistic is proposed to test whether the varying coefficients are constant. The asymptotic null distribution of the statistic is obtained and a residual-based bootstrap procedure is employed to compute thep-value of the statistic. Some simulations are conducted to evaluate the performance of the proposed methods. The results show that the estimating and testing procedures work well in finite samples.