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半变系数模型改进的轮廓最小二乘估计 被引量:1

The Improved Profile Least-squares Estimation of Semi-varying Coefficient Models
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摘要 针对半变系数模型,在局部线性拟合轮廓最小二乘估计方法的基础上将关于变系数函数的局部线性拟合改进为局部非线性拟合,得到半变系数模型改进的轮廓最小二乘估计,进一步讨论了常值系数的渐进正态性. This paper proposes a new improved profile least-squares estimation for fitting the semi-varying coefficient models by using the local nonlinear fitting means. The asymptotical normality of these estimators are established.
出处 《数学的实践与认识》 北大核心 2017年第15期249-253,共5页 Mathematics in Practice and Theory
基金 国家自然科学基金青年基金项目(51308115) 河南省高等学校重点科研项目(15A110050)
关键词 半变系数模型 局部非线性拟合 轮廓最小二乘估计 渐进正态性 semi-varying coefficient models local nonlinear fitting means profile least-squares estimation asymptotical normality
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