rolliter: Iterative Rolling Mean
In AkselA/R-rollfun:

Description Usage Arguments See Also Examples

Apply an iterative rolling mean

1	rolliter(x, w = 5, iter = 4, partial = FALSE, sharp = FALSE)

`x`	numeric; data vector
`w`	integer; width of the rolling window
`partial`	logical; should partial results at the beginning/end be calculated?
`sharp`	logical; experimental option. Should window width be reduced by one for each iteration?

iema

# Increasing the number of iterations progressively reduces the ringing
set.seed(1)
l <- 50
r <- rnorm(l) + rpois(l, (1:l/10))
w <- 6
plot(r, type="p", cex=0.5, pch=16)
points(rolliter(r, w, 1, partial=TRUE), type="o", col="orange", cex=0.5, pch=16)
points(rolliter(r, w, 2, partial=TRUE), type="o", col="hotpink", cex=0.5, pch=16)
points(rolliter(r, w, 3, partial=TRUE), type="o", col="purple", cex=0.5, pch=16)
points(rolliter(r, w, 4, partial=TRUE), type="o", col="blue", cex=0.5, pch=16)


# When w is even and i is odd the smoothed vector is shifted half a position
# to the left relative to the input vector
y <- c(rep(0, 18), 1, rep(0, 18))
col <- rainbow(20, start=0.2)
plot(y, ylim=c(0, 0.25))

for (i in 1:length(col)) {
    lines(rolliter(y, 4, i, partial=TRUE), col=col[i])
}


# Smoothing a binomial series with high missingness
set.seed(1)
z <- rbinom(100, 1, prob=seq(0.8, 0.2, length.out=100))
z[sample(as.logical(0:1), length(z), replace=TRUE, prob=c(0.6, 0.4))] <- NA

plot(z)

lines(rolliter(z, 6, 1, partial=TRUE), col="grey80")
lines(rolliter(z, 6, 2, partial=TRUE), col="grey60")
lines(rolliter(z, 6, 4, partial=TRUE), col="grey30")
lines(rolliter(z, 6, 6, partial=TRUE), col="black")


# Using the experimental sharp=TRUE appears to give a sharper transition while
# still keeping high frequency ringing at a low level
par(mfcol=c(4, 2), mar=c(2, 2, 1, 1), oma=c(0, 0, 0.5, 0))
set.seed(1)
r <- tanh(rnorm(2e4, 0, 0.4))
w <- 11
it <- c(2, 3, 6, 9)
s <- expand.grid(it=it, sharp=c(FALSE, TRUE))

for (i in 1:nrow(s)) {
	ri <- rolliter(r, w, s$it[i], partial=TRUE, sharp=s$sharp[i])
	spectrum(na.omit(ri), xlim=c(0, 0.5), ylim=c(1e-20, 1), xaxs="i",
	  main=ifelse(i %% 4 == 1, paste0("sharp=", s$sharp[i]), ""))
	grid(col="#00000066")
	text(0.005, 1e-20, paste0("w = ", w, "\n", "i = ", s$it[i]), adj=c(0, 0))
}