pcaRes {pcaMethods} | R Documentation

## Class for representing a PCA result

### Description

This is a class representation of a PCA result

### Details

Creating Objects
`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

scores

  "matrix", the calculated scores

loadings

  "matrix", the calculated loadings

R2cum

  "numeric", the cumulative R2 values

sDev

  "numeric", the individual standard deviations of the score vectors

R2

  "numeric", the individual R2 values

cvstat

  "numeric", cross-validation statistics

nObs

  "numeric", number of observations

nVar

  "numeric", number of variables

centered

  "logical", data was centered or not

center

  "numeric", the original variable centers

scaled

  "logical", data was scaled or not

scl

  "numeric", the original variable scales

varLimit

  "numeric", the exceeded variance limit

nPcs,nP

  "numeric", the number of calculated PCs

method

  "character", the method used to perform PCA

missing

  "numeric", the total amount of missing values in original data

completeObs

  "matrix", the estimated complete observations

network

  "nlpcaNet", the network used by non-linear PCA

Methods (not necessarily exhaustive)

print

  Print function

summary

  Extract information about PC relevance

screeplot

  Plot a barplot of standard deviations for PCs

slplot

  Make a side by side score and loadings plot

nPcs

  Get the number of PCs

nObs

  Get the number of observations

cvstat

  Cross-validation statistics

nVar

  Get the number of variables

loadings

  Get the loadings

scores

  Get the scores

dim

  Get the dimensions (number of observations, number of features)

centered

  Get a logical indicating if centering was done as part of the model

center

  Get the averages of the original variables.

completeObs

  Get the imputed data set

method

  Get a string naming the used PCA method

sDev

  Get the standard deviations of the PCs

scaled

  Get a logical indicating if scaling was done as part of the model

scl

  Get the scales of the original variablesb

R2cum

  Get the cumulative R2

### Author(s)

Henning Redestig

[Package pcaMethods version 1.72.0 Index]