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。
The experimental results show that the proposed SORR algorithm is better than the normal regression estimation algorithm of SVM.
结果表明SORR优于标准的支持向量机回归估计算法。
It was proven theoretically that the estimate errors of unbiased regression estimation are less than that of general regression estimation.
提出了无偏回归估计方法，从理论上证明了该法比常规的估计法具有更小的平均估计误差。
Firstly, we introduce the research situation of the local polynomial regression estimation and its basic concept from the model's background.
首先，从产生背景入手，介绍了非参数局部多项式回归估计模型的基本概念以及研究概况。
Fan J and Gijbels I gave the asymptotic normality of local polynomial regression estimation in dependent time series, where the weighted function is bounded.
对相依时间序列数据，在一定的条件下已有人证明了局部多项式加权回归系数估计服从渐近正态分布，其中核函数是有界的。
Now, how to design fast and efficient SVM algorithms applied to regression estimation becomes a great challenge in practical applications of support vector machine.
目前，如何设计快速有效的回归估计算法仍然是支持向量机实际应用中的问题之一。
SVM is the hot issue accompanying artificial neural network in machine learning. It involves any practical problems such as classification and regression estimation.
支持向量机是继神经网络后机器学习的热点研究技术，它主要应用于分类和回归问题中。
SVM is a kind of general learning algorithms, which has been widely used in pattern recognition, regression estimation, function approximation, density estimation, etc.
支撑矢量机是一种普适的算法，已经广泛地用于模式识别、回归估计、函数逼近、密度估计等方面。
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。
Figure 12: Illustration of regression-based technique for estimation.
图12：基于回归的评估技术。
When determining empirical formula with test method, estimation value of estimated parameter in regression equation which is obtained with least square method always is a long number.
用实验方法确定经验公式时，回归方程中用最小二乘方法求得的待估参数的估计值往往是一个很长的数。
Ridge Regression Analysis is a nonlinear partial estimation method.
岭回归分析是一种非线性的有偏估计方法。
Generalized Estimation Equation (GEE) was used to estimate parameters of poisson regression model.
采用了通用估计方程(GEE)方法对泊松回归模型进行参数估计。
By using LINGO software, coefficients can be estimated for linear least absolute deviations regression quickly and accurately, making it an effective approach to coefficient estimation.
利用LINGO软件能够快速、准确地估计出最小一乘线性回归的参数，从而使其成为一种有效的参数估计方法。
The parameter estimation method is multiple linear regression analysis.
参数估计法采用多元线性回归分析法。
Objective: the purpose of this study was to compare the performance of regression on order statistics(ROS) and substitution methods in estimation of nondetects.
目的：比较用于处理包含未检出值的痕量测定数据的次序统计量回归方法与经典替换方法的估计效果。
This research result in efficient regression testing by helping testers decide what classes and methods need to be retested, and in supporting cost estimation and schedule planning.
本文的研究能帮助程序开发人员在回归测试中确定需要重测的类和方法和成本估算及制定进度计划。
The prediction formula and its error estimation are also established. Its regression and time-varying autoregression model is presented.
在此基础上建立时变序列预测公式及误差估计公式，给出其回归与时变自回归模型。
On the data including the discrete points, least square estimation can not control the strong error affecting the regression curve.
在含有离群值的情况下，分析了最小二乘估计不能克服粗大误差对回归曲线的影响。
This article researches the coefficient estimating problem of the linear regression model and the math analysis foundation of the least squares estimation applying in the coefficient estimating.
本文研究了线性回归模型中的参数估计问题，运用最小二乘法进行参数估计的数学分析基础。
The kernel regression method now is the most popular non-parametric estimation method.
核回归方法是比较常用的一种非参数估计方法。
The estimation of adjusted population attributable risk is 5.31% based on the multivariable logishc regression model analysis.
在该多变量回归模型的基础上估计的调整人群归因风险度为5．31％。
Model parameters are computed using a weighted linear regression technology according to the different impacts of rate point to estimation of model parameters.
利用率点对模型参数估计的影响强弱，使用一种加权的线性回归模型参数估计算法。
We make analyses of the three hypotheses of regression. Adaptive adjustment of smoothing index parameters and parameter estimation of ARMA models.
对统计算法中回归模型中的假设条件、平滑指数的自适应调整、ARMA模型的参数估计作了一些分析。
This paper considers the estimation in the linear regression model under the criterion of minimizing the sum of absolute errors.
本文考虑在绝对误差和最小准则下的线性回归模型估计。
The elementary statistics include the statistics concept, data collection and analysis, estimation and hypothesis testing, analysis of variance, regression etc.
本课程包括统计基本概念、统计资料收集及分析、基本机率分配、估计与检定、变异数分析、线性回归等。
A robust parameters estimation algorithm is proposed in this paper, which is based on uniform design for a linear regression model in the case of its coefficient matrix with random disturbance.
针对一个线性回归模型的系统矩阵存在的随机扰动情况，提出一种基于均匀设计的稳健参数估计算法。
In this paper, on the basis of structural regression models the estimation of the population-averaged treatment effects is given when the response variable is a multi-dimensional vector.
在可交换条件下，当响应变量为多维时，利用结构回归模型研究总体平均处理效应的估计。
Simulation results and real measuring data calculations show that the precision estimation efficiency can be obtained by our method for a large class of linear and nonlinear regression models.
仿真和实算结果表明，对于一大类线性和非线性回归模型，该方法给出的回归模型的参数估计效率的估计更接近模型参数估计效率的真值。
Simulation results and real measuring data calculations show that the precision estimation efficiency can be obtained by our method for a large class of linear and nonlinear regression models.
仿真和实算结果表明，对于一大类线性和非线性回归模型，该方法给出的回归模型的参数估计效率的估计更接近模型参数估计效率的真值。
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