Apply a Function Over Adjacent Subsets of a Vector
Applies a function over subsets of the vector(s) formed by taking a fixed number of previous points.
running(X, Y=NULL, fun=mean, width=min(length(X), 20),
allow.fewer=FALSE, pad=FALSE, align=c("right", "center","left"),
simplify=TRUE, by, ...)X |
data vector |
Y |
data vector (optional) |
fun |
Function to apply. Default is |
width |
Integer giving the number of vector elements to include in the subsets. Defaults to the lesser of the length of the data and 20 elements. |
allow.fewer |
Boolean indicating whether the function should be
computed for subsets with fewer than |
pad |
Boolean indicating whether the returned results should
be 'padded' with NAs corresponding to sets with less than
|
align |
One of "right", "center", or "left".
This controls the relative location of ‘short’ subsets with less
then |
simplify |
Boolean. If FALSE the returned object will be a list containing one element per evaluation. If TRUE, the returned object will be coerced into a vector (if the computation returns a scalar) or a matrix (if the computation returns multiple values). Defaults to FALSE. |
by |
Integer separation between groups. If |
... |
parameters to be passed to |
running applies the specified function to
a sequential windows on X and (optionally) Y. If
Y is specified the function must be bivariate.
List (if simplify==TRUE), vector, or matrix containing the
results of applying the function fun to the
subsets of X (running) or X and Y.
Note that this function will create a vector or matrix even for
objects which are not simplified by sapply.
Gregory R. Warnes greg@warnes.net, with contributions by Nitin Jain nitin.jain@pfizer.com.
# show effect of pad running(1:20, width=5) running(1:20, width=5, pad=TRUE) # show effect of align running(1:20, width=5, align="left", pad=TRUE) running(1:20, width=5, align="center", pad=TRUE) running(1:20, width=5, align="right", pad=TRUE) # show effect of simplify running(1:20, width=5, fun=function(x) x ) # matrix running(1:20, width=5, fun=function(x) x, simplify=FALSE) # list # show effect of by running(1:20, width=5) # normal running(1:20, width=5, by=5) # non-overlapping running(1:20, width=5, by=2) # starting every 2nd # Use 'pad' to ensure correct length of vector, also show the effect # of allow.fewer. par(mfrow=c(2,1)) plot(1:20, running(1:20, width=5, allow.fewer=FALSE, pad=TRUE), type="b") plot(1:20, running(1:20, width=5, allow.fewer=TRUE, pad=TRUE), type="b") par(mfrow=c(1,1)) # plot running mean and central 2 standard deviation range # estimated by *last* 40 observations dat <- rnorm(500, sd=1 + (1:500)/500 ) plot(dat) sdfun <- function(x,sign=1) mean(x) + sign * sqrt(var(x)) lines(running(dat, width=51, pad=TRUE, fun=mean), col="blue") lines(running(dat, width=51, pad=TRUE, fun=sdfun, sign=-1), col="red") lines(running(dat, width=51, pad=TRUE, fun=sdfun, sign= 1), col="red") # plot running correlation estimated by last 40 observations (red) # against the true local correlation (blue) sd.Y <- seq(0,1,length=500) X <- rnorm(500, sd=1) Y <- rnorm(500, sd=sd.Y) plot(running(X,X+Y,width=20,fun=cor,pad=TRUE),col="red",type="s") r <- 1 / sqrt(1 + sd.Y^2) # true cor of (X,X+Y) lines(r,type="l",col="blue")
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