1) robust principal component regression
稳健主成分回归
1.
Methods We introduce a robust principal component regression based on MVT and LMS to detect outliers,and compare methods using a practical example.
方法采用基于MVT和LMS方法的一种稳健主成分回归方法来诊断异常点,并结合实例进行方法的对比。
3) robust regression
稳健回归
1.
Research on the software cost estimation based on the robust regression algorithm;
基于稳健回归技术的软件成本估计方法
2.
Considering the uncertainty which may be occurring in the simulation of a stamping process,the outlier of response is allowed and a stochastic response surface method(SRSM) based on robust regression was presented.
充分考虑到冲压成形数值模拟中可能出现的不确定性波动,允许响应量中存在异常响应,提出一种基于稳健回归的随机响应面法。
3.
In this paper, the peak load forecasting method based on robust regression is proposed by analyzing the peculiarities of the peak load.
在分析高峰负荷特点的基础上,建立了基于稳健回归模型的高峰负荷预测方法。
4) principal component regression
主成分回归
1.
Research on simultaneous determination of monocyclic and polycyclic aromatic hydrocarbons in white oil by principal component regression method;
主成分回归法同时测定白油中单环及多环芳烃含量
2.
Simultaneous determination of calcium and magnesium in food by principal component regression spectrophotometry;
主成分回归-分光光度法同时测定食品中的钙、镁
3.
Simultaneous determination of vitamin B with principal component regression;
主成分回归法同时测定维生素B
5) Principle component regression
主成分回归
1.
In this paper, a new algorithm for multivariate calibration named principle component regression based on wavelet (PCRW) is proposed.
将小波变换与主成分回归相结合,提出一种新型多元校正算法——小波基主成分回归法。
2.
A new method is proposed for the voidage measurement of gas-oil two-phase flow, based on principle component regression (PCR) and partial least squares regression (PLSR), with the capacitances from 12-electrode Electrical Capacitance Tomography (ECT) system.
本文利用12电极ECT系统提供的电容测量信息,基于主成分回归(PCR)和偏最小二乘回归(PLSR)技术,提出了一种油气两相流空隙率测量的新方法。
3.
Ridge regression(RR,principle component regression(PCR) and partial least square regression(PLSR) can all alleviate or eliminate the negative effects of collinearity at some degrees,but all fail in preceding other methods on theories and modeling effects.
结果表明,变量筛选法在处理共线性问题时,会将一些重要的解释变量排除在模型之外,从而削弱了理论的优先地位和导向功能;岭回归、主成分回归和偏最小二乘回归都能够不同程度地减轻或消除自变量共线性的不良影响,但均不能在理论和建模效果上一致地优于其他方法。
6) PCR
主成分回归
1.
With the methods of multi variety linear regression analysis and principal component regression analysis, the result showed that when n=3, two steps derivatived the whole spectrum PCR result close to the actual value ( SEP=0.
采用了多元线性回归分析与主成分回归分析方法 ,结果表明 ,当n =3时 ,二阶导数差谱的全光谱CR检测结果最接近真实值 (SEP=0 。
2.
PCR(principal component regress)that with the characters of reducing dimensions effectively and overcoming the intense relativity between independent variables, is widely used in different fields.
主成分回归以其能够有效的降低维数,克服回归问题中的自变量高度相关而产生的分析困难,而得到广泛的利用。
3.
Then we make use of the principal component regression(PCR) to calculate the comprehensive mark and rating points.
然后通过主成分回归法(PCR)计算出各高校的综合得分及排名,最后利用模糊聚类检验法和灰色关联分析法对结果进行了检验,证明了该评价体系的可靠性。
补充资料：主成分回归分析
分子式：
CAS号：
性质：以主成分为自变量进行的回归分析。是分析多元共线性问题的一种方法。用主成分得到的回归关系不像用原自变量建立的回归关系那样容易解释。
CAS号：
性质：以主成分为自变量进行的回归分析。是分析多元共线性问题的一种方法。用主成分得到的回归关系不像用原自变量建立的回归关系那样容易解释。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
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