plot.corregp: Plotting Correspondence Regression

In corregp: Functions and Methods for Correspondence Regression

Description

Basic method to plot the output of a correspondence regression.

Usage

## S3 method for class 'corregp'
plot(x, axes = 1:2, y_btm = TRUE, y_ell = FALSE,
  x_ell = FALSE, ysub = NULL, xsub = NULL, hlim = NULL, vlim = NULL,
  expa_btm = 1, expa_top = 1, asp = 1, asp_btm = asp, asp_top = asp,
  col_btm = "darkgrey", col_top = "red", cex_btm = par("cex"),
  cex_top = cex_btm, font_btm = par("font"), font_top = font_btm,
  fam_btm = par("family"), fam_top = fam_btm, col_ell = par("col"),
  lwd_ell = par("lwd"), lty_ell = par("lty"), col_ori = par("col"),
  lwd_ori = par("lwd"), lty_ori = 1, main = NULL, sub = NULL,
  hlab = NULL, vlab = NULL, cl = 0.95, np = 100, add_ori = TRUE, ...)

Arguments

x	The output of a call to corregp (i.e. an object of class "corregp").
axes	The axes to plot: a vector of two values. Defaults to the first two axes.
y_btm	Logical specifying whether the Y levels should be plotted first ("at the bottom") and then be overlaid by the X levels. Defaults to TRUE.
y_ell	Logical specifying whether the confidence ellipses of the Y levels should be plotted. Defaults to FALSE.
x_ell	Logical specifying whether the confidence ellipses of the X levels should be plotted. Defaults to FALSE.
ysub	Vector of indices to select a subset of the Y levels.
xsub	Vector of indices to select a subset of the X levels.
hlim	Vector of two values specifying the lower and upper limit between which to plot the horizontal axis.
vlim	Vector of two values specifying the lower and upper limit between which to plot the vertical axis.
expa_btm	Expansion factor for the bottom coordinates: a number to rescale the axes.
expa_top	Expansion factor for the top coordinates: a number to rescale the axes.
asp	The aspect ratio for the whole plot. See plot.window.
asp_btm	The aspect ratio for the bottom coordinates. See plot.window.
asp_top	The aspect ratio for the top coordinates. See plot.window.
col_btm	Color of the bottom levels: either numeric or see colors. Defaults to "darkgrey".
col_top	Color of the top levels: either numeric or see colors. Defaults to "red".
cex_btm	Character expansion factor of the bottom levels: a number to specify the size of the text labels.
cex_top	Character expansion factor of the top levels: a number to specify the size of the text labels.
font_btm	Font of the bottom levels: 1 for plain, 2 for bold, 3 for italic, and 4 for bold italic. Defaults to 1.
font_top	Font of the top levels: 1 for plain, 2 for bold, 3 for italic, and 4 for bold italic. Defaults to 1.
fam_btm	Font family of the bottom levels: can be "serif", "sans", "mono" or one of the Hershey fonts.
fam_top	Font family of the top levels: can be "serif", "sans", "mono" or one of the Hershey fonts.
col_ell	Color of the confidence ellipses: either a number or see colors.
lwd_ell	Width of the confidence ellipses: a number to specify the line width.
lty_ell	Line type of the confidence ellipses: 0 or "blank", 1 or "solid", 2 or "dashed", 3 or "dotted", 4 or "dotdash", 5 or "longdash", 6 or "twodash". Defaults to 1.
col_ori	Color of the lines through the origin: either numeric or see colors.
lwd_ori	Width of the lines through the origin: a number to specify the line width.
lty_ori	Line type of the lines through the origin: 0 or "blank", 1 or "solid", 2 or "dashed", 3 or "dotted", 4 or "dotdash", 5 or "longdash", 6 or "twodash". Defaults to 1.
main	The main title of the plot.
sub	The subtitle of the plot.
hlab	The title of the horizontal axis.
vlab	The title of the vertical axis.
cl	The confidence level for the confidence ellipses. Defaults to 0.95.
np	The number of points to represent the confidence ellipses. Defaults to 100.
add_ori	Logical specifying whether to add lines through the origin. Defaults to TRUE.
...	Further arguments passed to or from other methods.

Details

The plot of a correspondence regression is by definition a biplot.

Value

A plot window containing the output of a correspondence regression.

References

Gower, J., S. Lubbe and N. Le Roux (2011) Understanding biplots. Chichester: Wiley.

Greenacre, M. (2010) Biplots in practice. Bilbao: Fundacion BBVA.

See Also

corregp, summary.corregp, screeplot.corregp, anova.corregp, biplot.

Examples

data(HairEye)
haireye.crg <- corregp(Eye ~ Hair * Sex, data = HairEye, b = 3000)
plot(haireye.crg, x_ell = TRUE, xsub = c("Hair", "Sex"))

corregp documentation built on May 1, 2019, 10:08 p.m.