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], 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)) })