Biplot_English: Biplot graph.

In MVar: Multivariate Analysis

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)

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