helio.plot: Helio Plots

Description

Displays data using a circular layout; function is designed to be used with cca objects, but could perhaps be rigged for use in other circumstances.

Usage

helio.plot(c, cv = 1, xvlab = c$xlab, yvlab = c$ylab, 
    x.name = "X Variables", y.name = "Y Variables", lab.cex = 1,
    wid.fact = 0.75, main = "Helio Plot", 
    sub = paste("Canonical Variate", cv, sep = ""), zero.rad = 30, 
    range.rad = 20, name.padding = 5, name.cex = 1.5, 
    axis.circ = c(-1, 1), x.group = rep(0, dim(c$xstructcorr)[1]),
    y.group = rep(0, dim(c$ystructcorr)[1]), type = "correlation")

Arguments

object to be plotted (generally output from cca.

the canonical variate to display.

xvlab

X variable labels.

yvlab

Y variable labels.

x.name

name for the X variable set.

y.name

name for the Y variable set.

lab.cex

character expansion for plot labels.

wid.fact

width multiplier for data bars.

main

plot main title.

sub

plot subtitle.

zero.rad

radius for the zero-value reference circle.

range.rad

difference between inner and outer plotting radius.

name.padding

offset for variable names.

name.cex

character expansion for variable names.

axis.circ

location to draw axis circles.

x.group

optional grouping vector for X variables.

y.group

optional grouping vector for Y variables.

type

one of “correlation” or “variance”, depending on the type of data to be displayed.

Value

None.

Details

Helio plots display data in radial bars, with larger values pointing outward from a base reference circle and smaller (more negative) values pointing inward). Such plots are well-suited to the display of multivariate information with several groups of variables, as with canonical correlation analysis.

Examples

Run this code

# NOT RUN {
data(LifeCycleSavings)
pop <- LifeCycleSavings[, 2:3]
oec <- LifeCycleSavings[, -(2:3)]
cca.fit <- cca(pop, oec)

#Show loadings on first canonical variate
helio.plot(cca.fit, x.name="Population Variables", 
    y.name="Economic Variables")

#Show variances on second canonical variate
helio.plot(cca.fit, cv=2, x.name="Population Variables", 
    y.name="Economic Variables", type="variance")
# }