英语释义

• a case of multiple regression in which the predictor variables are themselves highly correlated

片语

multicollinearity diagnosis多重共线性诊断

exact multicollinearity[统计]

extreme multicollinearity[数]

partial multicollinearity部分多重共线性

no multicollinearity无多重共线性

complete multicollinearity完全多重共线性

approximate multicollinearity共线性

near multicollinearity多重共线性

Perfect multicollinearity[数] 完全多元共线性

英汉例句

• this time the results are wonderful and it gets the most appropriate regression models moreover the multicollinearity does not exist any more.

  得出了最佳的回归模型，而且完全消除了多重共线性的影响。

• for both gram-schmidt method and adjoint matrix method of mts, multicollinearity is solved by improving mahalanobis distance function.

  不管是马氏田口的施密特正交化法，还是伴随矩阵法，都是通过改进马氏距离函数来解决强相关问题。

• pls2 regression successfully solve the multicollinearity problems among the indices, which indicates that the customer satisfaction indices computed are better and more reasonable.

  pls2回归较好地克服了各指标间的多重共线性问题，通过此方法求得的顾客满意度指数更準确、合理。

• based on this, an on-line evaluation model of process stability with statistical method and partial-least-square regression (plsr) was set up which overcome the multicollinearity of input parameters.

  采用统计分析和偏最小二乘回归方法提出了过程稳定性在线评价模型，克服了输入变量严重多重相关性的问题。

• the least square estimates are not reliable when there exists multicollinearity in adjustment model.

  当平差模型中存在复共线关系时，未知参数的最小二乘估计很不可靠。

• properly selecting parameters to avoid stronger multicollinearity is a key to efficient estimation of parameters.

  合理地选择参数，避免参数间的强复共线性，是参数有效估计的关键之一。

• further, on this basis we derived an instrumental variable regression model. after disregarding the effect of multicollinearity among the explanatory variables, we verify the accuracy of the results.

  并以此为基础，衍生出工具变量回归模型，在剔除了解释变量多重共线性的影响后，验证了结果的準确性。

• for the problem of multicollinearity and the number of explanatory variables rather than practical issues, s.

  针对变量多重相关性及解释变量多于样本点等实际问题，伍德（s。

• in chapter 5 i inquire into the influence analysis of variable selections in modeling through data , multicollinearity andmodel mis-specification.

  第五章探讨了建摸中变量选择的影响分析，刻划了数据、复共线性关系和模型错定对自变量选择的影响。

• especially, the advantages of the method are marked, while the variables xs multicollinearity being serious.

  特别，当变量x多重相关性突出时，本文方法效果显着。