| smoothEnds | 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], na.rm=TRUE).
In R versions 3.6.0 and earlier, missing values (NA)
in y typically lead to an error, whereas now the equivalent of
median(*, na.rm=TRUE) is used.
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, endrule = X)")
lines(ys, col = "light gray")
matlines(cbind(s7k, s7.,s7m), lwd = 1.5, lty = 1, col = col3)
eRules <- c("keep","constant","median")
legend("topleft", paste("endrule", eRules, sep = " = "),
col = col3, lwd = 1.5, lty = 1, bty = "n")
stopifnot(identical(s7m, smoothEnds(s7k, 7)))
## With missing values (for R >= 3.6.1):
yN <- y; yN[c(2,40)] <- NA
rN <- sapply(eRules, function(R) runmed(yN, 7, endrule=R))
matlines(rN, type = "b", pch = 4, lwd = 3, lty=2,
col = adjustcolor(c("red", "orange4", "orange1"), 0.5))
yN[c(1, 20:21)] <- NA # additionally
rN. <- sapply(eRules, function(R) runmed(yN, 7, endrule=R))
head(rN., 4); tail(rN.) # more NA's too, still not *so* many:
stopifnot(exprs = {
!anyNA(rN[,2:3])
identical(which(is.na(rN[,"keep"])), c(2L, 40L))
identical(which(is.na(rN.), arr.ind=TRUE, useNames=FALSE),
cbind(c(1:2,40L), 1L))
identical(rN.[38:41, "median"], c(289,289, 397, 470))
})
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