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 
Fig7.4n <- function()
{
#  postscript(file = "Fig7.4.ps", height = 6.5, width = 6.5, horiz = F)
  par(mfrow = c(2, 2), mar = c(1.5, 1.5, 1.5, 0.5), mgp = c(5, 0.4, 0))
  rs <- c(57, 14, 55, 51, 30, 0, 53, 44, 34, 53, 49, 2)
  .Random.seed <- rs
  x <- (1:128)/128
  f1 <- 2 * sin(2 * pi * x)
  f2 <- c(rep(0, 32), rep(4, 64), rep(0, 32))
  y1 <- f1 + rnorm(128)
  .Random.seed <- rs
  y2 <- f2 + rnorm(128)
  plot(x, y1)
  lines(x, wr(threshold(wd(y1, filter.number = 5), type = "soft", policy
                        = "manual", value = 1.669)))
  mtext("Minimax thresholding", side = 3, line = 0.1)
  plot(x, y2)
  lines(x, wr(threshold(wd(y2, filter.number = 5), type = "soft", policy
                        = "manual", value = 1.669)))
  mtext("Minimax thresholding", side = 3, line = 0.1)
  plot(x, y1)
  lines(x, wr(threshold(wd(y1, filter.number = 5), type = "soft")))
  mtext("Universal thresholding", side = 3, line = 0.1)
  plot(x, y2)
  lines(x, wr(threshold(wd(y2, filter.number = 5), type = "soft")))
  mtext("Universal thresholding", side = 3, line = 0.1)
#  graphics.off()
  NULL
}