# This script illustrates the effect of varying the span of the
# smoothing window in density estimation (kernel method of R
# implemented in function `density`.
# This is an adaptation of the example provided in ?tkrplot.
# Time-stamp: <2007-07-27 11:59:18 chl>
library(tkrplot) ## will also load the `tcltk` package
animate <- function (x, k="Sturges", sp) {
  # x  : vector of values to plot
  # k  : number of breaks required for the histogram (default
  #      to R's settings, i.e. "Sturges"
  # sp : span of the smoothing window (parameter `adj`
  #      in `density`
  bb <- sp
  xx <- seq(min(x),max(x),length=length(x))
  cols <- c("gray60","blue")
  tt <- tktoplevel()
  # prepare the main panel
  img <-tkrplot(tt,
                function () {
                  hist(x,breaks=k,proba=T,ylim=c(0,.45))                 
                  lines(xx,dnorm(xx,mean=mean(x),sd=sd(x)),
                                col=cols[1],lwd=2)
                  lines(density(x,adj=bb),col=cols[2],lwd=3)
                  legend("topright",
                         c(paste("Normal N(",round(mean(x),0),",",
                                 round(sd(x),0),")",sep=""),
                           "Density Est."),
                         lty=rep(1,2),lwd=c(2,3),col=cols,bty="n")
                })
  # update graphics with new parameters
  # Note:
  # I need to fix this comparison which generates warnings
  f <- function (...) {
    b <- as.numeric(tclvalue("bb"))
    if (b != bb) {
      bb <<- b
      tkrreplot(img)
    }
  }
  # main loop
  s <- tkscale(tt, command=f, from=sp[1], to=sp[2], variable="bb",
               showvalue=TRUE, resolution=0.05, orient="horiz")
  tkpack(img,s)
}

# we generate contaminated normal observations
# see Venables (2002, 4th Ed., p. 111)
y <- rnorm(100,0,(1+2*rbinom(100,1,0.35))) 
animate(y, sp=c(.5,3))