Fast averaging over subset of vector elements
Computes the sample mean of all or a subset of values.
mean2(x, idxs = NULL, na.rm = FALSE, refine = TRUE, ...) meanOver(...)
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).
Returns a numeric scalar.
Henrik Bengtsson
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))
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