非参数回归函数的核估计近年来已有了一些研究。
The kernel estimate of nonparametric regression function has been researched recently.
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。
In this paper, a nonparametric regression model is established for the inflation of China, and a satisfying fitting result is obtained.
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。
This paper gives a new kernel estimate, bandwidth parameter and the bias-corrected confidence belt for nonparametric regression curve.
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。
Objective To improve on classical least squares estimate of regression analysis and explore nonparametric smoothing spline regression analysis.
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 suggests a new AGARCH linear regression model, and USES nonparametric regression method to estimate the model.
非参数回归模型因其能够描述许多数据自身所体现的非线性特征而受到人们的广泛关注。
Nonparametric regressive model has gained much attention recently, primarily due to the fact that they can describe some nonlinear features exhibited by many datas itself in applications.
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。
Based on the locally kernel weighted least squares fit of the nonparametric regression models, this paper presents the nonparametric testing method for nonlinear cointegration.
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。
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.
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。
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.
给出非参数回归模型中估计量的渐近偏差和渐近方差，并在适当条件下利用大小分块的思想获得了该估计量的渐近正态性。
Given the asymptotic bias and the asymptotic variance of estimation, moreover obtained the asymptotic normality of the estimation under certain condition using small-block and large-block arguments.
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。
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。
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.
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