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| Fast efficient estimation and application of partially linear single index model with fixed effects |
| DING Fei-peng, CHEN Jian-bao |
1. School of Mathematics and Information Science, Jiangxi Normal University, Nanchang 330022,China;
2. College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350117, China;
3. Fujian Provincial Engineering Technology Research Center for Public Service, Fuzhou 350117,China
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Abstract By combination of least square vector machine (LSSVM) with quadratic inference func-
tions (QIF), this paper construct a new estimation method for partially linear single index panel model
with fixed effects when responses from the same cluster are correlated. Under some regular condition,
asymptotic normality of parametric estimators and convergence rate of non-parametric estimator are
derived. The ˉnite sample performances of the proposed method are investigated by Monte Carlo simu-
lation under di?erent correlation structures, and compared with penalized quadratic inference functions
method (PQIF). The proposed estimation techniques are applied to analyse the relationship between
population structure and residents’consumption rate. Our research results show that the e±ciency
of estimators are improved by the proposed method, application e?ects are good, program operation
has high speed, it is particularly suitable for analysis of linear, nonlinear relationship among economic
variables and big data.
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Published: 04 July 2019
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固定效应部分线性单指数面板模型的快速有效估计及应用
将最小二乘支持向量机(LSSVM)和二次推断函数法(QIF)相结合, 构造了
个体内具有相关结构的固定效应部分线性单指数面板模型的新估计方法; 在一定
的正则条件下, 证明了参数估计量的渐近正态性, 导出了非参数估计量的收敛速度;
Monte Carlo模拟了所述方法在各种相关结构下的有限样本表现, 并与惩罚二次推断
函数(PQIF)法进行了比较; 将估计技术应用于分析我国人口结构与居民消费率的关
系. 研究发现, 该方法改善了估计量的有效性, 应用效果良好, 程序运行速度快, 适合经
济变量间的线性和非线性关系研究以及大数据分析.
关键词：
固定效应部分线性单指数面板模型,
最小二乘支持向量机,
二次推导函数法,
渐近性,
Monte Carlo模拟
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