The value of the interpolation fraction, typically (but not necessarily) 0 <= alpha <= 1).
xlim, ylim
x, y limits for the plot. If not specified, the function uses the
ranges of rbind(xy1, xy2).
points
Logical. Whether to plot the points in the current interpolation?
col
Color for plotted points.
add
Logical. Whether to add to an existing plot?
ellipse
logical. TRUE to plot a dataEllipse
ellipse.args
other arguments pqassed to dataEllipse
abline
logical. TRUE to plot the linear regression line for XY
col.lines
line color
lwd
line width
id.method
How points are to be identified. See showLabels.
labels
observation labels
id.n
Number of points to be identified. If set to zero, no points are identified.
id.cex
Controls the size of the plotted labels. The default is 1
id.col
Controls the color of the plotted labels.
segments
logical. TRUE to draw lines segments from xy1 to xy
segment.col
line color for segments
...
other arguments passed to plot()
Details
Interpolations other than linear can be obtained by using a non-linear series of
alpha values. For example alpha=sin(seq(0,1,.1)/sin(1) will give
a sinusoid interpolation.
Value
Returns invisibly the interpolated XY points.
Note
The examples here just use on-screen animations to the console graphics window.
The animation package provides facilities to save these in various formats.
Author(s)
Michael Friendly
See Also
dataEllipse,
showLabels,
animation
Examples
#################################################
# animate an AV plot from marginal to conditional
#################################################
data(Duncan, package="car")
duncmod <- lm(prestige ~ income + education, data=Duncan)
mod.mat <- model.matrix(duncmod)
# function to do an animation for one variable
dunc.anim <- function(variable, other, alpha=seq(0, 1, .1)) {
var <- which(variable==colnames(mod.mat))
duncdev <- scale(Duncan[,c(variable, "prestige")], scale=FALSE)
duncav <- lsfit(mod.mat[, -var], cbind(mod.mat[, var], Duncan$prestige),
intercept = FALSE)$residuals
colnames(duncav) <- c(variable, "prestige")
lims <- apply(rbind(duncdev, duncav),2,range)
for (alp in alpha) {
main <- if(alp==0) paste("Marginal plot:", variable)
else paste(round(100*alp), "% Added-variable plot:", variable)
interpPlot(duncdev, duncav, alp, xlim=lims[,1], ylim=lims[,2], pch=16,
main = main,
xlab = paste(variable, "| ", alp, other),
ylab = paste("prestige | ", alp, other),
ellipse=TRUE, ellipse.args=(list(levels=0.68, fill=TRUE, fill.alpha=alp/2)),
abline=TRUE, id.n=3, id.cex=1.2, cex.lab=1.25)
Sys.sleep(1)
}
}
# show these in the R console
if(interactive()) {
dunc.anim("income", "education")
dunc.anim("education", "income")
}
############################################
# correlated bivariate data with 2 outliers
# show rotation from data space to PCA space
############################################
set.seed(123345)
x <- c(rnorm(100), 2, -2)
y <- c(x[1:100] + rnorm(100), -2, 2)
XY <- cbind(x=x, y=y)
rownames(XY) <- seq_along(x)
XY <- scale(XY, center=TRUE, scale=FALSE)
# start, end plots
dataEllipse(XY, pch=16, levels=0.68, id.n=2)
mod <- lm(y~x, data=as.data.frame(XY))
abline(mod, col="red", lwd=2)
pca <- princomp(XY, cor=TRUE)
scores <- pca$scores
dataEllipse(scores, pch=16, levels=0.68, id.n=2)
abline(lm(Comp.2 ~ Comp.1, data=as.data.frame(scores)), lwd=2, col="red")
# show interpolation
# functions for labels, as a function of alpha
main <- function(alpha) {if(alpha==0) "Original data"
else if(alpha==1) "PCA scores"
else paste(round(100*alpha,1), "% interpolation")}
xlab <- function(alpha) {if(alpha==0) "X"
else if(alpha==1) "PCA.1"
else paste("X +", alpha, "(X - PCA.1)")}
ylab <- function(alpha) {if(alpha==0) "Y"
else if(alpha==1) "PCA.2"
else paste("Y +", alpha, "(Y - PCA.2)")}
interpPCA <- function(XY, alpha = seq(0,1,.1)) {
XY <- scale(XY, center=TRUE, scale=FALSE)
if (is.null(rownames(XY))) rownames(XY) <- 1:nrow(XY)
pca <- princomp(XY, cor=TRUE)
scores <- pca$scores
for (alp in alpha) {
interpPlot(XY, scores, alp,
pch=16,
main = main(alp),
xlab = xlab(alp),
ylab = ylab(alp),
ellipse=TRUE, ellipse.args=(list(levels=0.68, fill=TRUE, fill.alpha=(1-alp)/2)),
abline=TRUE, id.n=2, id.cex=1.2, cex.lab=1.25, segments=TRUE)
Sys.sleep(1)
}
}
# show in R console
if(interactive()) {
interpPCA(XY)
}
## Not run:
library(animation)
saveGIF({
interpPCA(XY, alpha <- seq(0,1,.1))},
movie.name="outlier-demo.gif", ani.width=480, ani.height=480, interval=1.5)
## End(Not run)