Plot.PCA {MVar} | R Documentation |
Graphs of the Principal Components Analysis (PCA).
Description
Graphs of the Principal Components Analysis (PCA).
Usage
Plot.PCA(PC, titles = NA, xlabel = NA, ylabel = NA, size = 1.1,
grid = TRUE, color = TRUE, linlab = NA, axes = TRUE, class = NA,
classcolor = NA, posleg = 2, boxleg = TRUE, savptc = FALSE,
width = 3236, height = 2000, res = 300, casc = TRUE)
Arguments
PC |
Data of the PCA function. |
titles |
Titles of the graphics, if not set, assumes the default text. |
xlabel |
Names the X axis, if not set, assumes the default text. |
ylabel |
Names the Y axis, if not set, assumes the default text. |
size |
Size of the points in the graphs. |
grid |
Put grid on graphs (default = TRUE). |
color |
Colored graphics (default = TRUE). |
linlab |
Vector with the labels for the observations. |
axes |
Plots the X and Y axes (default = TRUE). |
class |
Vector with names of data classes. |
classcolor |
Vector with the colors of the classes. |
posleg |
0 with no caption, |
boxleg |
Puts the frame in the caption (default = TRUE). |
savptc |
Saves graphics images to files (default = FALSE). |
width |
Graphics images width when savptc = TRUE (defaul = 3236). |
height |
Graphics images height when savptc = TRUE (default = 2000). |
res |
Nominal resolution in ppi of the graphics images when savptc = TRUE (default = 300). |
casc |
Cascade effect in the presentation of the graphics (default = TRUE). |
Value
Returns several graphs.
Author(s)
Paulo Cesar Ossani
Marcelo Angelo Cirillo
See Also
Examples
data(iris) # data set
data <- iris[,1:4]
cls <- iris[,5] # data class
pc <- PCA(data, 2)
tit <- c("Scree-plot","Observations","Correlations")
cls <- as.character(iris[,5])
Plot.PCA(PC = pc, titles = tit, xlabel = NA, ylabel = NA,
color = TRUE, linlab = NA, savptc = FALSE, size = 1.1,
posleg = 2, boxleg = FALSE, class = cls, axes = TRUE,
classcolor = c("blue3","red","goldenrod3"),
width = 3236, height = 2000, res = 300, casc = FALSE)