apply_sweep: Slight modifications of apply() and sweep()

In UncDecomp: Uncertainty Decomposition

Description

Slightly modified version of apply() and sweep(). apply0() and sweep0() are modification of apply() and sweep() so that they can be used when the length(MARGIN) is zero. msweep() is a modification of sweep() so that it can be used when function receives multiple summary statistic.

Usage

apply0(X, MARGIN, FUN, ...)

sweep0(X, MARGIN, STATS, FUN, ...)

msweep(X, MARGIN, STATS, FUN, ...)

Arguments

X	an array.
MARGIN	apply0() : a vector giving the subscripts which the function will be applied over. sweep0(), msweep() : a vector of indices giving the extent(s) of x which correspond to STATS.
FUN	the function to be applied. For msweep(), a function that receives the elements of X and list in order
...	further arguments passed to or from other methods.
STATS	the summary statistic array which is to be swept out. For msweep(), list of summary statistic array.

Value

If each call to FUN returns a vector of length n, then apply() returns an array of dimension c(n, dim(X)[MARGIN]) if n > 1. If n equals 1, apply() returns a scalar if MARGIN has length 0, a vector if MARGIN has length 1 and an array of dimension dim(X)[MARGIN] otherwise. sweep0() and msweep() return an array with the same shape as x, but with the summary statistics swept out.

Examples

set.seed(0)
A <- array(rnorm(24), dim = 4:2)
meanA0 <- apply0(A, numeric(0), mean)
meanA12 <- apply0(A, 1:2, mean)
sdA12 <- apply0(A, 1:2, sd)
ctrArray <- function(a,mu) return(a-mu)
sweep0(A, numeric(0), meanA0, ctrArray)
sweep0(A, 1:2, meanA12, ctrArray)
statsA12 <- list(meanA12, sdA12)
stdArray <- function(a,mu,sigma) return((a-mu)/sigma)
msweep(A, 1:2, statsA12, stdArray)

UncDecomp documentation built on Nov. 7, 2019, 5:09 p.m.