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regression coefficient中文是什么意思
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- 中文翻译
- 造句
- 回归系数
- 回旭系数
- regression n. 1.复归，回归。 2.退步，退化。 3.【天文学】 ...
- coefficient adj. 共同作用的。 n. 1.共同作用；协同因素。 ...
- coefficient of regression 回归系数
- coefficient of multiple regression 复回归系数
- coefficient of net regression 净回归系数
- coefficient of partial regression 偏回归系数
- common regression coefficient 公共回归系数
- estimate of regression coefficient 回归系数估计
- multiple regression coefficient 复回归系数
- net regression coefficient 净回归系数
- parametric regression coefficient 参数回归系数
- parent-offspring regression coefficient 亲代子代回归系数
- partial regression coefficient 偏回归系数
- path regression coefficient 因径回归系数
- population regression coefficient 总体回归系数
- regression coefficient test 回归系数检验
- regression-like coefficient 回归型系数
- sample partial regression coefficient 样品偏回归系数
- sample regression coefficient 样本回归系数; 样品回归系数
- significance of regression coefficient 回归系数显著性
- simple regression coefficient 单回归系数
- standard partial regression coefficient 标准偏回归系数
- standard regression coefficient 标准回归系数
- standardized regression coefficient 标准化回归系数
- total regression coefficient 总回归系数; 总加归系数
- With mathematical proofs and hypothetical data , this paper demonstrated that when there are more than 2 ivs , inference on the relative importance of these ivs should not be made from standardized regression coefficients ( s ) alone
本文以假设性的数据为例，配合数学演算证明：当自变项超过两个时，标准化?归系数并不适合作为评断自变项相对重要性的唯一依据。 - In . the practical application , the second linear regression equation of this sur system is usually regarded as auxiliary information of the first one , and . all of the results of unknown regression coefficient 2 are parallel to that of 1
在实际应用中， sur系统的第二个线性回归方程一般是为第一个方程提供辅助信息，且未知回归系数_ 2的所有结果与_ 1平行。 - Velocity variation is positively correlated with crust thickness and negatively correlated with earth ' s heatflow . the linear regression equation of velocity , crust thichness and heatflow is obtained . the regression coefficient dv / dp convert
同时地震波速厂与地壳厚度h呈明显的线性正相关关系，与大地热流呈负相关关系，并得到三者的线性回归方程，回归系数dv dh换算成bv op ？ - The method is applied to shenzhen pumped storage power plant , the regression coefficients corresponding to the in - situ stress factors are determined by fitting the stress measured values , and the initial stress field is obtained for the rock mass of whole engineering
并以深圳抽水蓄能电站为实例，通过拟合实测地应力资料获得对应于地应力构成因素的回归系数，并得到整个工程区的岩体初始应力场。 - The main results are as follows : according to the approximate multicollinearity of matrix , the third chapter constrains the regression coefficient and obtains generalized ridge estimation of the linear model ' s parameter under the ellipsoidal restriction
主要结果如下：论文第三章从设计矩阵的多重共线性角度出发，考虑回归系数的椭球约束，获得了椭球约束下线性模型参数的一种新型估计- -广义岭型估计。 - Starting with the equivalence condition of admissibility , this paper discusses respectively the linear biased estimate of the regression coefficient of thee models : the g - m linear regression model , the multivariate linear regression and the mixed - effect coefficient linear model
本文以可容许性的等价条件为起点，分别讨论了g - m线性回归模型、多元线性回归模型和混合系数线性模型的回归系数的一类线性有偏估计。 - The correlation between factors and land use change is discussed and multivariable regression model is set up . by means of standardized regression coefficient of the model , impact of main driving forces on arable land change is analyzed quantitatively
根据驱动因子与土地利用变化关系的分析，提出表征县域土地利用变化驱动因子的指标体系，分析了二者的相关关系，建立了多元回归模型，并以其标准回归系数为指标定量分析了驱动因子对耕地变化的影响。 - This paper analyzes the factors affecting the controlling precision of sand compactibility system and sets up the dynamic model of regression coefficient between sand compactibility and water content . to prevent the insufficiency or excess of sand water content , the amount of the first addition is set as 80 % of the total water addition amount . after the first water addition , we adopt ar model to predict the stable value of sand compactibility to shorten the time mixing the sand . each time we add water , the correction coefficient is introduced to adapt to the change in the composition of sand . the experiment shows that the mathematics model not only makes the water content in sand reach the best range within shorter time , but also directs how the sand composition should be adjusted , which can better conform to the actual situation
分析了影响型砂紧实率控制精度的因素，建立了型砂紧实率-水分回归系数的动态模型.为防止型砂水分不足或过量，将第一次加水量设定为总加水量的80 .第一次加水后，对型砂紧实率稳定值采用ar模型进行预测，以缩短型砂混制时间.每次加水后，引入修正系数，以适应型砂组成的变化.实验表明，该数学模型不仅使型砂水分含量在较短时间内达到最佳范围，同时可指示对型砂组成进行调整，能较好地符合实际情况 - We make the following assumption for when 2 is positive definite matrix , different estimators about matrix of regression coefficients and inefficiency of least squares estimate have been discussed in many documents . considered 2 is nonnegative definite matrix , this thesis derives best linear unbiased estimate of parameter matrix b and estimable parameter function kbl under the meaning of matrix nonnegative definite and the property of maximum probability of blue is investigated . next , we discuss some necessary and sufficient conditions of the equality of the lse and blue , then we derive the estimation of the deviation bet - ween the least squares and the best linear unbias estimators of the mean matrix , meanwhile a relative efficiency of lse ofb is proposed and its bound is given
当0时，众多文献讨论了回归系数阵的各种估计及lse的有效性，本文考虑了当0的情形，给出了回归系数阵b及其可估参数函数kbl的在矩阵非负定意义下的最优估计( blue ) ，研究了它的一个最大概率性质，并且讨论了最小二乘估计成为最佳线性无偏估计的充分必要条件，在此基础上给出了均值矩阵的最小二乘估计与blue的偏差估计，定义了lse相对于blue的一个相对效率，并给出了它的界。 - However , two - stage estimates of regression coefficients corresponding to these two estimates have approximate equal mean square error . for testing linear hypothesis about regression coefficients , banerjee and magnus ( 1997 ) studied the sensitivity of f - test sta , tistic ( fgls ( ) ) based on generalized least square estimate caused by variance parameter in general case and proposed sensitivity statistic and its distribution
关于回归系数的线性假设检验问题， banerjee和magnus ( 1997 )在一般情况下从理论上研究了方差参数对基于广义最小二乘估计的f -检验统计量( f _ ( gls ) ( ) )的种种影响，提出了敏感性的概念，并给出敏感统计量的形式及其分布。
- 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
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