smoothEnds {stats} | R Documentation |
Smooth end points of a vector y
using subsequently smaller
medians and Tukey's end point rule at the very end. (of odd span),
smoothEnds(y, k = 3)
y |
dependent variable to be smoothed (vector). |
k |
width of largest median window; must be odd. |
smoothEnds
is used to only do the ‘end point smoothing’,
i.e., change at most the observations closer to the beginning/end
than half the window k
. The first and last value are computed using
Tukey's end point rule, i.e.,
sm[1] = median(y[1], sm[2], 3*sm[2] - 2*sm[3])
.
vector of smoothed values, the same length as y
.
Martin Maechler
John W. Tukey (1977) Exploratory Data Analysis, Addison.
Velleman, P.F., and Hoaglin, D.C. (1981) ABC of EDA (Applications, Basics, and Computing of Exploratory Data Analysis); Duxbury.
runmed(*, endrule = "median")
which calls
smoothEnds()
.
require(graphics) y <- ys <- (-20:20)^2 y [c(1,10,21,41)] <- c(100, 30, 400, 470) s7k <- runmed(y, 7, endrule = "keep") s7. <- runmed(y, 7, endrule = "const") s7m <- runmed(y, 7) col3 <- c("midnightblue","blue","steelblue") plot(y, main = "Running Medians -- runmed(*, k=7, end.rule = X)") lines(ys, col = "light gray") matlines(cbind(s7k, s7.,s7m), lwd = 1.5, lty = 1, col = col3) legend(1, 470, paste("endrule", c("keep","constant","median"), sep = " = "), col = col3, lwd = 1.5, lty = 1) stopifnot(identical(s7m, smoothEnds(s7k, 7)))