stats (version 3.3.1)

smoothEnds: End Points Smoothing (for Running Medians)

Description

Smooth end points of a vector y using subsequently smaller medians and Tukey's end point rule at the very end. (of odd span),

Usage

smoothEnds(y, k = 3)

Arguments

y

dependent variable to be smoothed (vector).

k

width of largest median window; must be odd.

Value

y.

Details

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]).

References

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.

See Also

runmed(*, endrule = "median") which calls smoothEnds().

Examples

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)))