The kernel estimate of nonparametric regression function has been researched recently.
非参数回归函数的核估计近年来已有了一些研究。
This paper mainly studies the nonparametric regression estimation model of local polynomial.
论文主要研究了非参数局部多项式回归估计模型。
This paper suggests a new AGARCH linear regression model, and USES nonparametric regression method to estimate the model.
本文提出一个新的非对称广义arch模型，并以非参数回归方法对模型进行估计。
This paper gives a new kernel estimate, bandwidth parameter and the bias-corrected confidence belt for nonparametric regression curve.
对非参数回归曲线提出了一种新的核估计量和窗宽选择方法及修正偏倚置信带。
In this paper, a nonparametric regression model is established for the inflation of China, and a satisfying fitting result is obtained.
文章对我国通货膨胀建立非参数回归模型，取得了令人满意的拟合效果。
Through the use of linear model and nonparametric regression model, the trend of the total foreign exchange reserve account for the proportion of GDP is fitted.
利用线性模型和非参数回归模型，对我国外汇储备总量占国内GDP总量比重的变化走势进行了拟合分析。
A new nonparametric regression learning algorithm for RBF neural network is presented. It is a novel method involving a combination between regression trees and RBF networks.
介绍了一种新的非参数回归RBF神经网络学习算法，该算法将R BF神经网络与回归树结合起来使用。
Based on the locally kernel weighted least squares fit of the nonparametric regression models, this paper presents the nonparametric testing method for nonlinear cointegration.
本文基于非参数回归模型的局部核权最小二乘法提出变量间非线性协整的一种非参数检验方法。
So far, however, the theory that studies specially the statistical models with dependent data such as nonlinear regression and nonparametric regression models is not very satisfactory.
然而，对各种具体的相依数据的统计模型(如相依数据的非线性回归和相依数据的非参数回归模型)的研究还不够充分和不够完备。
Objective To improve on classical least squares estimate of regression analysis and explore nonparametric smoothing spline regression analysis.
目的改进回归分析的经典最小二乘估计方法和探讨光滑样条非参数回归分析方法。
Based on the local kernal weighted least squared fit of the nonparametric and additive regression model, this paper presents the nonparametric testing method for nonlinear cointegration.
本文基于非参数可加回归模型的局部核权最小二乘法提出变量间非线性协整的一种非参数检验方法。
And the nonparametric models is based on data, the form of its regression function is discretionary, so it has a great adaptability.
而非参数回归模型是基于数据本身，其回归函数的形式可以任意，因而有较大适应性。
This paper introduced the selection principle and method about a reasonable kernel function and bandwidth based on the nonparametric kernel density estimation and kernel regression estimation.
本文基于非参数核密度估计与核回归估计的基础上，介绍了合理选取核函数及窗宽的原则和方法。
This paper introduced the selection principle and method about a reasonable kernel function and bandwidth based on the nonparametric kernel density estimation and kernel regression estimation.
本文基于非参数核密度估计与核回归估计的基础上，介绍了合理选取核函数及窗宽的原则和方法。
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