mean2: Fast averaging over subset of vector elements

In matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors)

Fast averaging over subset of vector elements

Description

Computes the sample mean of all or a subset of values.

Usage

mean2(x, idxs = NULL, na.rm = FALSE, refine = TRUE, ...)

Arguments

x	An NxK matrix or, if dim. is specified, an N * K vector.
idxs	A vector indicating subset of elements to operate over. If NULL, no subsetting is done.
na.rm	If TRUE, missing values are excluded.
refine	If TRUE and x is numeric, then extra effort is used to calculate the average with greater numerical precision, otherwise not.
...	Not used.

Details

mean2(x, idxs) gives equivalent results as mean(x[idxs]), but is faster and more memory efficient since it avoids the actual subsetting which requires copying of elements and garbage collection thereof.

If x is numeric and refine = TRUE, then a two-pass scan is used to calculate the average. The first scan calculates the total sum and divides by the number of (non-missing) values. In the second scan, this average is refined by adding the residuals towards the first average. The mean() uses this approach. mean2(..., refine = FALSE) is almost twice as fast as mean2(..., refine = TRUE).

Value

Returns a numeric scalar.

Author(s)

Henrik Bengtsson

See Also

mean(). To efficiently sum over a subset, see sum2().

Examples

x <- 1:10
n <- length(x)

idxs <- seq(from = 1, to = n, by = 2)
s1 <- mean(x[idxs])                     # 25
s2 <- mean2(x, idxs = idxs)             # 25
stopifnot(identical(s1, s2))

idxs <- seq(from = n, to = 1, by = -2)
s1 <- mean(x[idxs])                     # 25
s2 <- mean2(x, idxs = idxs)             # 25
stopifnot(identical(s1, s2))

s1 <- mean(x)                           # 55
s2 <- mean2(x)                          # 55
stopifnot(identical(s1, s2))

matrixStats documentation built on Sept. 11, 2024, 5:24 p.m.