线性回归模型的拟合效果总体较差。
利用线性回归模型，可以预测TN含量的空间分布。
Spatial distribution of TN content could be forecasted by using linear regression model.
讨论设计矩阵列降秩时，线性回归模型的影响分析。
The influence of linear model with deficient - rank is discussed.
计算线性与非线性回归模型的能力是R的强大功能之一。
One of r's strengths is its ability to calculate linear, as well as nonlinear regression models.
通过多元线性回归模型，得出了多因子复合流变方程。
A multivariate regression equation was deduced with a multivariate linear regression model.
本文考虑在绝对误差和最小准则下的线性回归模型估计。
This paper considers the estimation in the linear regression model under the criterion of minimizing the sum of absolute errors.
在非寿险精算中，古典线性回归模型的假设很难得到满足。
In non-life insurance, the hypothesis of general linear model is hard to be satisfied.
给出基于最小一乘准则的非线性回归模型的参数估计算法。
In this paper, a parameters evaluation algorithm based on the least absolute criteria for non linear regress is developed.
广义线性回归模型分析表明，身心症状得分与睡眠状况有关系。
The score of physical and psychological symptoms are related to sleeping states.
给出了线性回归模型中的加权最小二乘估计以及最优权数的选择。
This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.
与线性回归模型及原bp网络模型相比，预测精度有了明显的改善。
Predicting precision of the networks was improved obviously compared with LR model and basic BP networks model.
精度检验合格，经比较该模型预测精度优于线性回归模型的预测精度。
The comparison demonstrates that the model is superior to linear regression model in precision.
本文提出一种克服线性回归模型系数矩阵病态的“紧致最小二乘估计”。
In this paper a "compact least square method" is presented to overcome the ill-conditioned coefficient matrices in the linear regression models.
本文给出了若干近似公式，以分析非线性回归模型的最小二乘估计的残差。
Several approximate formulas are given for residual analysis of the least square estimator in nonlinear regression model.
本文将讨论综合运用非线性回归模型和时间序列分析的方法进行变形预报。
This article demonstrates that deformation forecast will be performed by a comprehensive method of non linear regression model combined with time series analysis.
应用样本选择模型对模拟数据进行分析，并与传统线性回归模型进行比较。
The missing data were analysed with sample selection model and compared with traditional linear regression model.
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。
Model parameters are computed using a weighted linear regression technology according to the different impacts of rate point to estimation of model parameters.
对多元线性回归模型参数的预测，转化为对其变量集合的增广矩阵的叉积阵的预测。
Prediction to the regression parameters was converted to predict cross product matrix of the variable augmented matrix.
将识别问题看作是多个线性回归模型中的分类问题，并用稀疏表示理论解决这些问题。
The recognition problem is taken as one of classifying among multiple linear regression models, and sparse signal representation is used to solve this problem.
线性回归模型的建立，一个很重要的过程就是自变元的选择，它直接决定着模型的优劣。
Independent variable of selection decides directly the advantage and disadvantage of the model which is the very important process of the establishment of the linear regression model.
其次，在此评价指标体系的基础上，利用统计中的线性回归模型的方法建立了评价模型。
Secondly, based on the system, evaluation model has set up by utilizing statistical linear regression model method.
针对温度对废气氧传感器输出的影响，建立了带温度校正的EGO传感器非线性回归模型。
For the influence of temperature to EGO sensor's output, its nonlinear regression models which include temperature's modifying term be achieved.
多元线性回归模型分析显示：血清tc水平与累积噪声剂量呈正相关，与高温级别呈负相关。
The multiple liner regression model indicated that serum TC level was significantly associated with accumulative noise dose, but negative associate with scale of hot environment.
对一般线性回归模型中有关参数估计分布的模拟问题，给出一种随机加权逼近的再构造方法。
A reconstructing method for random weighting approximations is proposed in approach to the distributions of the parameter estimates in general linear regression model.
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。
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.
在误差为相依的情况下，讨论了线性回归模型的刀切最小二乘估计与广义刀切最小二乘估计。
This paper studies linear regression models with dependent errors, and we introduce the jackknifed least squares estimator and generalized jackknife least squares estimator.
主要考虑了同方差型的半参数线性回归模型中参数的随机加权最小二乘估计（RWLSE）。
The randomly weighted least square estimator (RWLSE) for the parametric component in semi-parametric regression models was mainly discussed.
提出了采用动态结焦模型以及新鲜催化剂结焦速率的线性回归模型来估计结焦模型参数的方法。
A dynamic catalyst coking model and multi-variant linear regression model are used to estimate the parameters of catalyst coking model.
考虑了几个主要经济因素对居民用电量的影响，并用历史数据拟合出用电量多元线性回归模型。
This paper considers the effects of some economic factors to residential electricity consumption, and builds the multiple liner regressive equations MLRE using historical data.
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。
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.
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