特别，当变量X多重相关性突出时，本文方法效果显著。
Especially, the advantages of the method are marked, while the variables Xs multicollinearity being serious.
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。
For the problem of multicollinearity and the number of explanatory variables rather than practical issues, s.
为了克服多重相关性对模型的干扰，引入了能辨别系统信息与噪声的偏最小二乘回归，并编制了程序。
To avoid multicollinearity's disturbance, partial least-squares regression which can identify system information and noise is introduced to model, and a program is compiled.
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。
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.
为了克服多重相关性对模型的干扰，本文引入了能辨别系统信息与噪声的偏最小二乘回归，并提出了一种基于偏最小二乘回归原理的土石坝渗流监控模型。
To avoid multicollinearity's disturbance, partial least-squares regression which can identify system information and noise is introduced to model, and a novel seepage monitoring model is introduced.
计算结果表明，睡眠脑电序列具有长程相关性，而且是多重分形过程。
The result shows that the sleep EEG series has the multifractal features as well as long range correlation.
目的了解采用双纸片协同法进行CTX - M酶的表型检测与多重pcr法检测基因型的相关性。
Objective to investigate the correlation between phenotypic confirmatory by double disc test and genotype of CTX-M-enzymes detected by multiplex polymerase chain reaction (PCR).
本文从哲学的角度分析了当代人类面临的生存危机的新特点—多重性和全球性、相关性和渗透性、严峻性和紧迫性；
The new characteristics of the crisis of human existence of our time are discussed philosophically in this paper. It includes multiplicity, globalism, correlation, infiltration, severity, and urgency.
其中北京株的结核分枝感菌不但具高盛行率，同时与多重抗药性、广泛抗药性的高发生率有相关性，因此这株菌对亚洲地区而言特别具有威胁性。
Of particular threat to the Asian community is the high prevalence of the Beijing strain and is associated with higher frequencies of multidrug resistance (MDR) and extensive drug resistance (XDR).
同时，考虑到特质波动率和相关性这两个因素和一些影响市场收益率的因素相关，不加任何处理就引入定价模型，可能导致自变量之间的多重共线性。
At the same time, considering these two factors correlated with other factors that influence market return, there may be co-linearity in our regression equations if we ignore this phenomena.
同时，考虑到特质波动率和相关性这两个因素和一些影响市场收益率的因素相关，不加任何处理就引入定价模型，可能导致自变量之间的多重共线性。
At the same time, considering these two factors correlated with other factors that influence market return, there may be co-linearity in our regression equations if we ignore this phenomena.
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