In this paper, a new process of estimating autocorrelation parameter is given when remedying autocorrelation of error term in regression model.
在消除回归模型误差项的自相关现象的处理中，提出了一种确定自相关参数估计值的新方法。
A reconstructing method for random weighting approximations is proposed in approach to the distributions of the parameter estimates in general linear regression model.
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。
Based on the basic principle and modeling method of partial least-square regression (PLSR), establishing the mathematical model for parameter prediction of the steam turbine units.
根据偏最小二乘回归的基本原理和建模的基本思路，建立数学模型并将其应用于电厂机组的参数预测中。
Stochastic parameter sensitivity of SRM grain structure was analyzed based on viscoelastic stochastic finite element method(VSFEM) and polynomial regression model.
基于粘弹性随机有限元法（VSFEM）和多项式回归模型，分析了固体火箭发动机药柱结构的随机参数灵敏度。
At realm of surface roughness of machined surface, forecast mathematical model is set up by using quadratic regression orthogonal design between NC turning parameter and machined surface.
在已加工表面粗糙度研究领域引入回归正交分析，采用多元二次回归正交设计得到了数控车削参数与已加工表面粗糙度的回归预报模型。
Parameter tuning of Support Vector Regression (SVR) has been a critical task to develop a SVR model with good generalization performance.
在回归支持向量机的建模中，参数调节问题一直是影响模型性能的重要因素之一。
Algorithms for iteratively refining the parameter estimates and residuals from the fitting of a regression model using QR decomposition are described.
讨论用QR分解拟合回归方程时，参数估计和剩余的迭代加细算法。
The calculating formulae of weighted optimum curve regression model parameter given in this paper possesses high speed of parameter correcting, high precision of fitting and obvious effect.
本文给出的带权优化曲线回归模型参数计算公式，修正参数速度快，拟合精度高，效果显著。
In this paper, we will consider the universal admissibility for linear estimators of regression coefficients under growth curve model with respect to restricted parameter sets.
本文讨论带约束生长曲线模型中回归系数线性估计的泛容许性，给出了回归系数的线性估计在线性估计类中是泛容许估计的充要条件。
Finally, a quadratic regression equation is used to represent LTV system, and the GA and AIC are introduced to determine the structure of the parameter sub-model.
然后利用遗传算法和AIC确定参数子模型的结构，以获得最终用于表示LTV系统的二次回归方程。
On the condition of reaching the target desulfurization efficiency, optimal operating parameter has been put forward based on this multivariate regression model.
并通过最优模型得出的参数关系，在达到目标脱硫效率的条件下，提出了优化运行的参数值。
On the condition of reaching the target desulfurization efficiency, optimal operating parameter has been put forward based on this multivariate regression model.
并通过最优模型得出的参数关系，在达到目标脱硫效率的条件下，提出了优化运行的参数值。
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