PcaHubert-class(rrcov)
PcaHubert-class()所属R语言包:rrcov
Class "PcaHubert" - ROBust method for Principal Components Analysis
“PcaHubert类” - 强大的主成分分析方法
译者:生物统计家园网 机器人LoveR
描述----------Description----------
The ROBPCA algorithm was proposed by Hubert et al (2005) and stays for 'ROBust method for Principal Components Analysis'. It is resistant to outliers in the data. The robust loadings are computed using projection-pursuit techniques and the MCD method. Therefore ROBPCA can be applied to both low and high-dimensional data sets. In low
ROBPCA算法,提出了由Hubert等人(2005年),并保持有强大的主成分分析方法“。是耐离群点数据中。强劲的荷载是使用投影追求技术和MCD方法计算的。 ,因此ROBPCA可以施加到低和高维数据集。在低
类对象----------Objects from the Class----------
Objects can be created by calls of the form new("PcaHubert", ...) but the usual way of creating PcaHubert objects is a call to the function PcaHubert which serves as a constructor.
可以通过检测的形式new("PcaHubert", ...)“可是通常的方式创建”PcaHubert对象是PcaHubert作为构造函数的功能调用创建的对象。
插槽----------Slots----------
alpha: Object of class "numeric" the fraction of outliers
alpha:对象类"numeric"部分的异常值
quan: Object of class "numeric" The quantile h used throughout the algorithm
quan:类的对象"numeric"的位数h用于整个算法
from the "Pca" class.
从"Pca"类。
扩展----------Extends----------
Class "PcaRobust", directly. Class "Pca", by class "PcaRobust", distance 2.
类"PcaRobust",直接。类"Pca",类的“PcaRobust”,距离2。
方法----------Methods----------
getQuan signature(obj = "PcaHubert"): Returns the quantile
getQuan signature(obj = "PcaHubert"):返回位数
(作者)----------Author(s)----------
Valentin Todorov <a href="mailto:valentin.todorov@chello.at">valentin.todorov@chello.at</a>
参考文献----------References----------
An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. URL http://www.jstatsoft.org/v32/i03/.
参见----------See Also----------
PcaRobust-class, Pca-class, PcaClassic, PcaClassic-class
PcaRobust-class,Pca-class,PcaClassic,PcaClassic-class
实例----------Examples----------
showClass("PcaHubert")
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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