Biplot {MVar}

Biplot graph.

Description

Plots the Biplot graph.

Usage

Biplot(data, alpha = 0.5, title = NA, xlabel = NA, ylabel = NA,
       size = 1.1, grid = TRUE, color = TRUE, var = TRUE,
       obs = TRUE, linlab = NA, class = NA, classcolor = NA,
       posleg = 2, boxleg = TRUE, axes = TRUE, savptc = FALSE, 
       width = 3236, height = 2000, res = 300)

Arguments

data

Data for plotting.

alpha

Representativeness of the individuals (alpha), representativeness of the variables (1 - alpha), being 0.5 the default.

title

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).

var

Adds the variable projections to graph (default = TRUE).

obs

Adds the observations to graph (default = TRUE).

linlab

Vector with the labels for the observations.

class

Vector with names of data classes.

classcolor

Vector with the colors of the classes.

posleg

0 with no caption,
1 for caption in the left upper corner,
2 for caption in the right upper corner (default),
3 for caption in the right lower corner,
4 for caption in the left lower corner.

boxleg

Puts the frame in the caption (default = TRUE).

axes

Plots the X and Y axes (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).

Value

Biplot

Biplot graph.

Md

Matrix eigenvalues.

Mu

Matrix U (eigenvectors).

Mv

Matrix V (eigenvectors).

coorI

Coordinates of the individuals.

coorV

Coordinates of the variables.

pvar

Proportion of the principal components.

Author(s)

Paulo Cesar Ossani

Marcelo Angelo Cirillo

References

Rencher, A. C. Methods of multivariate analysis. 2th. ed. New York: J.Wiley, 2002. 708 p.

Examples

data(iris) # dataset

data <- iris[,1:4]

Biplot(data)


cls <- iris[,5]
res <- Biplot(data, alpha = 0.6, title = "Biplot of data valuing individuals",
              class = cls, classcolor = c("goldenrod3","gray56","red"),
              posleg = 2, boxleg = FALSE, axes = TRUE, savptc = FALSE, 
              width = 3236, height = 2000, res = 300)
print(res$pvar)


res <- Biplot(data, alpha = 0.4, title = "Graph valuing the variables",
              xlabel = "", ylabel = "", color = FALSE, obs = FALSE,
              savptc = FALSE, width = 3236, height = 2000, res = 300) 
print(res$pvar)