|
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 |
Fig2.6 <- function()
{
# postscript(file = "Fig2.6.ps", horiz = F, height = 4.5, width = 3.5)
par(mfrow = c(3, 1), mar = c(1.5, 1.5, 1.5, 0.5), mgp = c(5, 0.4, 0))
rs <- c(25, 61, 59, 54, 11, 1, 20, 35, 11, 15, 41, 3)
.Random.seed <- rs
n <- 32
x <- (1:n)/n
y <- 1:(n/4)
y <- (c(y, rev(y), rep(0, n/2)) * 9)/(n/4)
xsca <- x * 2 * pi - pi
ynoise <- y + rnorm(n)
a0 <- (sum(ynoise) * 2)/n
a1 <- (sum(ynoise * cos(x * 2 * pi - pi)) * 2)/n
a2 <- (sum(ynoise * cos(2 * (x * 2 * pi - pi))) * 2)/n
a3 <- (sum(ynoise * cos(3 * (x * 2 * pi - pi))) * 2)/n
a4 <- (sum(ynoise * cos(4 * (x * 2 * pi - pi))) * 2)/n
a5 <- (sum(ynoise * cos(5 * (x * 2 * pi - pi))) * 2)/n
b1 <- (sum(ynoise * sin(x * 2 * pi - pi)) * 2)/n
b2 <- (sum(ynoise * sin(2 * (x * 2 * pi - pi))) * 2)/n
b3 <- (sum(ynoise * sin(3 * (x * 2 * pi - pi))) * 2)/n
b4 <- (sum(ynoise * sin(4 * (x * 2 * pi - pi))) * 2)/n
b5 <- (sum(ynoise * sin(5 * (x * 2 * pi - pi))) * 2)/n
npoints <- 150
u <- (0:(npoints - 1))/(npoints - 1)
usca <- u * 2 * pi - pi
plot(xsca, ynoise, ylim = c(min(ynoise), max(ynoise)))
lines(usca, a0/2 + a1 * cos(usca) + b1 * sin(usca))
mtext("J=1", side = 3, line = 0.1)
plot(xsca, ynoise, ylim = c(min(ynoise), max(ynoise)))
lines(usca, a0/2 + a1 * cos(usca) + b1 * sin(usca) + a2 * cos(2 * usca) +
b2 * sin(2 * usca) + a3 * cos(3 * usca) + b3 * sin(3 * usca))
mtext("J=3", side = 3, line = 0.1)
plot(xsca, ynoise, ylim = c(min(ynoise), max(ynoise)))
lines(usca, a0/2 + a1 * cos(usca) + b1 * sin(usca) + a2 * cos(2 * usca) +
b2 * sin(2 * usca) + a3 * cos(3 * usca) + b3 * sin(3 * usca) +
a4 * cos(4 * usca) + b4 * sin(4 * usca) + a5 * cos(5 * usca) +
b5 * sin(5 * usca))
mtext("J=5", side = 3, line = 0.1)
# graphics.off()
NULL
}