binMeans: Fast mean calculations in non-overlapping bins
In matrixStats: Methods that apply to rows and columns of a matrix

Description Usage Arguments Details Value Missing and non-finite values Author(s) References See Also Examples

Computes the sample means in non-overlapping bins

1 2	## Default S3 method: binMeans(y, x, bx, na.rm=TRUE, count=TRUE, right=FALSE, ...)

`y`	A `numeric` `vector` of K values to calculate means on.
`x`	A `numeric` `vector` of K positions for to be binned.
`bx`	A `numeric` `vector` of B+1 ordered positions specifying the B bins `[bx[1],bx[2])`, `[bx[2],bx[3])`, ..., `[bx[B],bx[B+1])`.
`na.rm`	If `TRUE`, missing values in `y` are dropped before calculating the mean, otherwise not.
`count`	If `TRUE`, the number of data points in each bins is returned as attribute `count`, which is an `integer` `vector` of length B.
`right`	If `TRUE`, the bins are right-closed (left open), otherwise left-closed (right open).
`...`	Not used.

binMeans(x, bx, right=TRUE) gives equivalent results as rev(binMeans(-x, bx=sort(-bx), right=FALSE)), but is faster.

Returns a numeric vector of length B.

Data points where either of y and x is missing are dropped. Non-finite values in y are not allowed and gives an error. Missing values in bx are not allowed and gives an error.

Henrik Bengtsson with initial code contributions by Martin Morgan [1].

[1] R-devel thread Fastest non-overlapping binning mean function out there? on Oct 3, 2012

binCounts(). aggregate and mean().

x <- 1:200
mu <- double(length(x))
mu[1:50] <- 5
mu[101:150] <- -5
y <- mu + rnorm(length(x))

# Binning
bx <- c(0,50,100,150,200)+0.5
yS <- binMeans(y, x=x, bx=bx)

plot(x,y)
for (kk in seq(along=yS)) {
  lines(bx[c(kk,kk+1)], yS[c(kk,kk)], col="blue", lwd=2)
}