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

Fig5.16s <- function()
{
#  postscript(file = "Fig5.16.ps", height = 3.9, width = 7.37, horiz = F)
  par(mfrow = c(1, 2), mar = c(1.5, 2.5, 1.5, 1.5), mgp = c(1.5, 0.4, 0))
  rs <- c(57, 14, 55, 51, 30, 0, 53, 44, 34, 53, 49, 2)
  .Random.seed <- rs
  blocky <- make.signal("blocks", n = 1024)
  sigma <- sqrt(var(blocky))/3
  bnoise <- blocky + rnorm(1024, sd = sigma)
  bnoisewt <- dwt(bnoise, wavelet = "d10")
  boxplot(bnoisewt$d5, bnoisewt$d4, bnoisewt$d3, bnoisewt$d2, bnoise$d1, 
          names = c("j=5", "j=6", "j=7", "j=8", "j=9"))
  mtext("Noisy blocky function", side = 3, line = 0.1)
  .Random.seed <- rs
  wn <- rnorm(1024)
  wnwt <- dwt(wn, wavelet = "d10")
  boxplot(wnwt$d5, wnwt$d4, wnwt$d3, wnwt$d2, wnwt$d1,
          names = c("j=5", "j=6", "j=7", "j=8", "j=9"))
  mtext("White noise", side = 3, line = 0.1)
#  graphics.off()
  NULL
}