Loadings plot for the results of PCA.Calculate

Description

Allows the user to plot a loadings plot for two components.

Usage

PCA.PlotLoadings(pr.object, pcs = c(1, 2))

Arguments

Value

Only the plot is returned.

Note

Output of ASCA.Calculate is required.

Author(s)

Tim Dorscheidt

Examples

##Plot selected loadings after doing PerformAsca
## use the data matrix, 'ASCAX', and an experimental design matrix, 'ASCAF'.
data(ASCAdata)
ASCA <- ASCA.Calculate(ASCAX, ASCAF, equation.elements = "1,2,12", scaling = TRUE)

## plot the loadings of the first two principal components of the first factor
ASCA.PlotLoadings(ASCA, ee = "1", pcs="1,2")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(MetStaT)
Loading required package: MASS
Loading required package: abind
Loading required package: pls

Attaching package: 'pls'

The following object is masked from 'package:stats':

    loadings

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MetStaT/PCA.PlotLoadings.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PCA.PlotLoadings
> ### Title: Loadings plot for the results of PCA.Calculate
> ### Aliases: PCA.PlotLoadings
> 
> ### ** Examples
> 
> ##Plot selected loadings after doing PerformAsca
> ## use the data matrix, 'ASCAX', and an experimental design matrix, 'ASCAF'.
> data(ASCAdata)
> ASCA <- ASCA.Calculate(ASCAX, ASCAF, equation.elements = "1,2,12", scaling = TRUE)
Variance explained per principal component (if >1%):
Whole data set 	PC1: 52.84%   PC2: 22.89%   PC3: 18.92%   PC4: 5.34%    
Factor 1     	PC1: 100.00%  PC2:  NA%     PC3:  NA%     PC4:  NA%     
Factor 2     	PC1: 91.34%   PC2: 8.66%    PC3:  NA%     PC4:  NA%     
Interaction 12	PC1: 88.72%   PC2: 11.28%   PC3:  NA%     PC4:  NA%     

Percentage each effect contributes to the total sum of squares:
Overall means  	0.96%
Factor 1     	0.00%
Factor 2     	0.00%
Interaction 12	0.00%
Residuals      	0.00%

Percentage each effect contributes to the sum of squares of the centered data:
Factor 1     	0.00%
Factor 2     	0.00%
Interaction 12	0.00%
Residuals      	0.00%

> 
> ## plot the loadings of the first two principal components of the first factor
> ASCA.PlotLoadings(ASCA, ee = "1", pcs="1,2")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>