Plot.CCA_English: Graphs of the Canonical Correlation Analysis (CCA).

In MVar: Multivariate Analysis

Graphs of the Canonical Correlation Analysis (CCA).

Description

Graphs of the Canonical Correlation Analysis (CCA).

Usage

Plot.CCA(CCA, titles = NA, xlabel = NA, ylabel = NA,
         size = 1.1, grid = TRUE, color = TRUE, savptc = FALSE, 
         width = 3236, height = 2000, res = 300, casc = TRUE)

Arguments

CCA	Data of the CCA 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).
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

CCA

Examples

data(DataMix) # database

data <- DataMix[,2:ncol(DataMix)]

rownames(data) <- DataMix[,1]

X <- data[,1:2]

Y <- data[,5:6]

res <- CCA(X, Y, type = 2, test = "Bartlett", sign = 0.05) # performs CCA

tit <- c("Scree-plot","Correlations","Scores of the group X","Scores of the group Y")

Plot.CCA(res, titles = tit, xlabel = NA, ylabel = NA,
         color = TRUE, savptc = FALSE, width = 3236, 
         height = 2000, res = 300, casc = TRUE)

MVar documentation built on Aug. 19, 2023, 5:12 p.m.