Plot.CA {MVar}

Graphs of the simple (CA) and multiple correspondence analysis (MCA).

Description

Graphs of the simple (CA) and multiple correspondence analysis (MCA).

Usage

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

Arguments

CA

Data of the CA 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.

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

CA

Examples

data(DataFreq) # frequency data set

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

rownames(data) <- DataFreq[1:nrow(DataFreq),1]

res <- CA(data, "f") # performs CA

tit <- c("Scree-plot","Observations", "Variables", "Observations / Variables")

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


data(DataQuali) # qualitative data set

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

res <- CA(data, "c", "b") # performs CA

tit <- c("","","Graph of the variables")

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