From: Gavin Simpson <gavin.simpson_at_ucl.ac.uk>

Date: Thu, 24 Jul 2008 15:27:15 +0100

}

sum.w <- sum(w)

sum.w2 <- sum(w^2)

mean.w <- sum(x * w) / sum(w)

(sum.w / (sum.w^2 - sum.w2)) * sum(w * (x - mean.w)^2, na.rm = na.rm)

}

}

sum.w <- sum(w)

(sum(w*x^2) * sum.w - sum(w*x)^2) / (sum.w^2 - sum(w^2)) }

Date: Thu, 24 Jul 2008 15:27:15 +0100

On Thu, 2008-07-24 at 02:25 +0530, Arun Kumar Saha wrote:

> There is a R function to calculate weighted mean : weighted.mean() under

*> stats package. Is there any direct R function for calculating weighted
**> variance as well?
*

Here are two ways; weighted.var() is via the usual formula and weighted.var2() uses a running sums approach. The formulae for which are both on the weighted mean entry page on wikipedia for example.

The removal of NA is as per weighted.mean, but I have not included any of the sanity checks that that functions contains.

weighted.var <- function(x, w, na.rm = FALSE) {

if (na.rm) {

w <- w[i <- !is.na(x)] x <- x[i]

}

sum.w <- sum(w)

sum.w2 <- sum(w^2)

mean.w <- sum(x * w) / sum(w)

(sum.w / (sum.w^2 - sum.w2)) * sum(w * (x - mean.w)^2, na.rm = na.rm)

}

weighted.var2 <- function(x, w, na.rm = FALSE) {

if (na.rm) {

w <- w[i <- !is.na(x)] x <- x[i]

}

sum.w <- sum(w)

(sum(w*x^2) * sum.w - sum(w*x)^2) / (sum.w^2 - sum(w^2)) }

## from example section in ?weighted.mean
## GPA from Siegel 1994

wt <- c(5, 5, 4, 1)/15

x <- c(3.7,3.3,3.5,2.8)

weighted.mean(x,wt)

weighted.var(x, wt)

weighted.var2(x, wt)

And some timings:

> system.time(replicate(100000, weighted.var(x, wt)))

user system elapsed

2.679 0.014 2.820

> system.time(replicate(100000, weighted.var2(x, wt)))

user system elapsed

2.224 0.010 2.315

**HTH
**
G

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