pcaRes(pcaMethods)
pcaRes()所属R语言包：pcaMethods
Class for representing a PCA result
一类为代表的PCA结果
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This is a class representation of a PCA result
这是一个类的PCA结果表示
Details
详情----------Details----------
Creating Objects<br> new("pcaRes", scores=[the scores], loadings=[the loadings], nPcs=[amount of PCs], R2cum=[cumulative R2], nObs=[amount of observations], nVar=[amount of variables], R2=[R2 for each individual PC], sDev=[stdev for each individual PC], centered=[was data centered], center=[original means], varLimit=[what variance limit was exceeded], method=[method used to calculate PCA], missing=[amount of NAs], completeObs=[estimated complete observations])
创建对象参考new("pcaRes", scores=[the scores], loadings=[the loadings], nPcs=[amount of PCs], R2cum=[cumulative R2], nObs=[amount of observations], nVar=[amount of variables], R2=[R2 for each individual PC], sDev=[stdev for each individual PC], centered=[was data centered], center=[original means], varLimit=[what variance limit was exceeded], method=[method used to calculate PCA], missing=[amount of NAs], completeObs=[estimated complete observations])
Slots<br>
插槽参考
scores "matrix", the calculated scores
分数“矩阵”，计算分数
loadings "matrix", the calculated loadings
负荷“矩阵”，计算负荷
R2cum "numeric", the cumulative R2 values
r2cum“数字”，累计R2值
sDev "numeric", the individual standard
发展局局长“数字”，个别标准
R2 "numeric", the individual R2 values
R2的“数字”，个别的R2值
cvstat "numeric", cross-validation statistics
cvstat“数字”，交叉验证统计
nObs "numeric", number of observations
NOBS“数字”的若干意见
nVar "numeric", number of variables
nvar的“数字”，变量的数目
centered "logical", data was centered or not
围绕“逻辑”，数据被集中或不
center "numeric", the original variable centers
中心的“数字”，原来的变量中心
scaled "logical", data was scaled or not
规模的“逻辑”，数据缩放或不
scl "numeric", the original variable scales
SCL“数字”，原来的变量尺度
varLimit "numeric", the exceeded variance limit
varLimit“数字”，超出的方差限制
nPcs,nP "numeric", the number of calculated PCs
筹备，NP“数字”，计算个人电脑的数量
method "character", the method used to perform PCA
法“性格”，用来进行主成分分析的方法
missing "numeric", the total amount of missing values in
缺少“数字”，缺失值总额
completeObs "matrix", the estimated complete observations
completeObs“矩阵”，估计完整的意见
network "nlpcaNet", the network used by non-linear PCA
网络“nlpcaNet”，由非线性PCA用于网络
Methods (not necessarily exhaustive)<br>
方法（不一定详尽）参考
print Print function
打印打印功能
summary Extract information about PC relevance
摘要电脑相关的信息提取
screeplot Plot a barplot of standard deviations for PCs
个人电脑的标准偏差为barplot screeplot图
slplot Make a side by side score and loadings plot
方得分和载荷图slplot设为一个侧面
nPcs Get the number of PCs
筹备获取电脑的数量
nObs Get the number of observations
NOBS获取的若干意见
cvstat Cross-validation statistics
cvstat交叉验证统计
nVar Get the number of variables
nvar的获取变量的数目
loadings Get the loadings
负载获取的负荷
scores Get the scores
成绩取得的成绩
dim Get the dimensions (number of observations, number of
昏暗的获取尺寸（若干意见，数
centered Get a logical indicating if centering was done as
集中获取逻辑表示如果定心做
center Get the averages of the original variables.
中心获得的原始变量的平均值。
completeObs Get the imputed data set
completeObs获取估算数据集
method Get a string naming the used PCA method
方法获取一个字符串，命名使用的PCA方法
sDev Get the standard deviations of the PCs
发展局局长获取的个人电脑的标准偏差
scaled Get a logical indicating if scaling was done as
缩放获取逻辑表示，如果缩放做
scl Get the scales of the original variablesb
SCL获取原始variablesb的鳞片
R2cum Get the cumulative R2
r2cum获取累计R2
作者（S）----------Author(s)----------
Henning Redestig
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-26 10:51:40
