1.
multicollinear regressor
多重共线性回归因子
2.
classical normal linear regression model
古典正态线性回归模型
3.
multiple normal linear regression mode
多重正态线性回归模型
4.
stochastic assumption of linear regression model
线性回归模型随机假设
5.
Returns the parameters of a linear trend
返回一线性回归拟合线性方程的参数
6.
The Conditional Root Squares Estimation of Regression Coefficient in Restricted Linear Regression Model;
约束线性回归模型回归系数的条件根方估计
7.
The Estimation Theory of Regression Coefficient in Linear Regression Model under Balanced Loss Function;
平衡损失下线性回归模型回归系数的估计理论
8.
The Balanced LS Estimation of the Regressive Coefficient in Linear Model and Its Prediction;
线性回归模型回归系数的平衡LS估计及预测
9.
Estimation on Regression Coefficient of Linear Regression Equation in L~p Space;
L~p空间上线性回归方程回归系数的估计
10.
Returns a value along a linear trend
通过一条线性回归拟合线来返回一个预测值
11.
Calculates, or predicts, a future value along a linear trend by using existing values
通过一条线性回归拟合线返回一个预测值
12.
An Practical Method in Linear Regression Significance Test;
一种线性回归显著性检验的实用方法
13.
Some problems on heteroscedasticity in multi-linear regression models;
多元线性回归模型中的异方差性问题
14.
The Eviews Diagnosis of Linear Regression Model Structure’s Stability
线性回归模型结构稳定性的Eviews诊断
15.
when the regression line is linear (y = ax + b) the regression coefficient is the constant (a) that represents the rate of change of one variable (y) as a function of changes in the other (x); it is the slope of the regression line.
线性回归分析中计算出来的回归线的常数和自变量的系数。
16.
Multicollinearity in Multilinear Regression Models and Partial Least Squares Regression;
多元线性回归中复共线问题及偏最小二乘回归分析
17.
highly multicollinear regressor
高度多重共线性回归自变量
18.
Examples of neural coding. Simple linear regression.
神经编码的例子与简单的线性回归。