tests/doc/lineplot/ridge.R

In directlabels: Direct labels for multicolor plots in lattice or ggplot2

## complicated ridge regression lineplot ex. fig 3.8 from Elements of
## Statistical Learning, Hastie et al.
myridge <- function(f,data,lambda=c(exp(-seq(-15,15,l=200)),0)){
  require(MASS)
  require(reshape2)
  fit <- lm.ridge(f,data,lambda=lambda)
  X <- data[-which(names(data)==as.character(f[[2]]))]
  Xs <- svd(scale(X)) ## my d's should come from the scaled matrix
  dsq <- Xs$d^2
  ## make the x axis degrees of freedom
  df <- sapply(lambda,function(l)sum(dsq/(dsq+l)))
  D <- data.frame(t(fit$coef),lambda,df) # scaled coefs
  molt <- melt(D,id=c("lambda","df"))
  ## add in the points for df=0
  limpts <- transform(subset(molt,lambda==0),lambda=Inf,df=0,value=0)
  rbind(limpts,molt)
}
data(prostate,package="ElemStatLearn")
pros <- subset(prostate,train==TRUE,select=-train)
m <- myridge(lpsa~.,pros)
library(lattice)
xyplot(value~df,m,groups=variable,type="o",pch="+",
       panel=function(...){
         panel.xyplot(...)
         panel.abline(h=0)
         panel.abline(v=5,col="grey")
       },
       xlim=c(-1,9),
       main="Ridge regression shrinks least squares coefficients",
       ylab="scaled coefficients",
       sub="grey line shows coefficients chosen by cross-validation",
       xlab=expression(df(lambda)))