Essential Wavelets for Statistical
Applications and Data Analysis

R.T. Ogden, University of South Carolina
0-8176-3864-4 * 1996 * $40.00 * Hardcover * 285 pages * 40 Illustrations

Fig2.3 <- function()
{
#  postscript(file = "Fig2.3.ps", height = 6.5, width = 6.5, horiz = F)
  par(mfrow = c(2, 2), mar = c(2.5, 1.5, 1.5, 0.5), mgp = c(5, 0.4, 0))
  ofdat <- c(4.37, 3.87, 4, 4.03, 3.5, 4.08, 2.25, 4.7, 1.73, 4.93, 1.73, 
             4.62, 3.43, 4.25, 1.68, 3.92, 3.68, 3.1, 4.03, 1.77, 4.08, 1.75,
             3.2, 1.85, 4.62, 1.97, 4.5, 3.92, 4.35, 2.33, 3.83, 1.88, 4.6, 
             1.8, 4.73, 1.77, 4.57, 1.85, 3.52, 4, 3.7, 3.72, 4.25, 3.58, 
             3.8, 3.77, 3.75, 2.5, 4.5, 4.1, 3.7, 3.8, 3.43, 4, 2.27, 4.4, 
             4.05, 4.25, 3.33, 2, 4.33, 2.93, 4.58, 1.9, 3.58, 3.73, 3.73, 
             1.82, 4.63, 3.5, 4, 3.67, 1.67, 4.6, 1.67, 4, 1.8, 4.42, 1.9, 
             4.63, 2.93, 3.5, 1.97, 4.28, 1.83, 4.13, 1.83, 4.65, 4.2, 3.93, 
             4.33, 1.83, 4.53, 2.03, 4.18, 4.43, 4.07, 4.13, 3.95, 4.1, 2.27,
             4.58, 1.9, 4.5, 1.95, 4.83, 4.12)
  densest(ofdat, lambda = 0.05)
  densest(ofdat, lambda = 0.1)
  densest(ofdat, lambda = 0.25)
  densest(ofdat, lambda = 0.75)
#  graphics.off()
  NULL
}

densest <- function(dat,lambda=0.5)
{
  x <- seq(0.8, 5.8, length = 300)
  y <- rep(0, length(x))
  for(i in 1:length(xx))
    y[i] <- sum(dnorm((xx[i] - dat)/lambda))/(n * lambda)
  plot(x, y, type = "l")
  mtext(side = 1, line = 1.3, paste("Bandwidth = ", lambda))
  NULL
}