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simple regression

英 [ˈsɪmpl rɪˈɡreʃn]

美 [ˈsɪmpl rɪˈɡreʃn]

网络  简单回归; 一元回归; 简单回归分析; 单回归

英英释义

noun

双语例句

  • Examples of neural coding. Simple linear regression.
    神经编码的例子与简单的线性回归。
  • ANOVA and simple regression analysis were used to measure three variables across four brands, four collaboration combinations and each of four brands independently.
    方差分析和回归分析被用来衡量三个变量,并适用于三个不同的层次,包括:四个品牌、四个合作组合和独立的四个品牌三个变量。
  • A Simple Regression Method& Three Point Method
    一种简单的回归方法&三点法
  • The simple linearity regression equation and multiple regression equation of single leaf area of apple-pear were inosculated by measuring and analysing their leave areas.
    通过对苹果梨单叶面积的测定与分析,拟合了单叶面积的简单线性回归方程与多元线性回归方程。
  • Using the simple linear regression, GARCH model and the various liquidity indicators, analyzed the impaction of interest rate adjustment to stock market.
    然后借助简单线性回归方程、GARCH模型和各种流动性指标来分析利率调整的未预期部分对股票市场的影响。
  • The estimations of the parameters and coefficient of contamination for the simple regression model are studied when its response variables are contaminated by another random variable sequence in [ 1] 、 [ 2]. But the proof is erroneous.
    文[1]、[2]研究了简单回归模型中响应变量受到另一随机变量序列污染时,模型参数和污染系数的估计方法,但在利用误差的不同阶矩估计给出污染系数的估计时发生了错误。
  • The Analysis on the Significant Testing Ways of the Simple Linear Regression
    一元线性回归显著性检验方法分析
  • Two main forms of virtual variable regression model is used in this paper, one simple linear regression model, the other is GARCH model.
    采用的虚拟变量回归模型有两种主要形式,一是简单线性回归模型,另一个是GARCH模型。
  • Starting with the three kind of error characteristics, the paper introduces simple linear regression theory and puts forward an influence coefficient calibration model with error correction function, and designs a amount of unbalance calibration algorithm which is rapid convergence and meets real-time requirement of online dynamic balance.
    从三种误差的特性入手,引入一元线性回归理论,提出了具有误差修正功能的影响系数标定模型,并设计了快速收敛的不平衡量标定算法,满足在线动平衡实时性要求。
  • Then, we may calculate actual figures of storage life for the product. This article shows five data analysis methods, which are simple linear regression, exponential regression, weighted exponential regression, polynomial regression ( method of least squares) and grey theory.
    本文采用一元线性回归、指数回归、加权指数回归、多项式回归(最小二乘法)和灰色理论等五种分析方法分别对五种试验数据进行了拟合与预测。