weighted.var: Compute a weighted variance or standard deviation of a...
In hadley/bigvis: Tools for visualisation of big data sets

Compute a weighted variance or standard deviation of a vector.

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weighted.var(x, w = NULL, na.rm = FALSE)

weighted.sd(x, w, na.rm = TRUE)

`x`	numeric vector of observations
`w`	integer vector of weights, representing the number of time each `x` was observed
`na.rm`	if `TRUE`, missing values in both `w` and `x` will be removed prior computation. Otherwise if there are missing values the result will always be missing.

Note that unlike the base R var function, these functions only work with individual vectors not matrices or data frames.

Other weighted statistics: weighted.ecdf; weighted.quantile

x <- c(1:5)
w <- rpois(5, 5) + 1
y <- x[rep(seq_along(x), w)]
weighted.var(x, w)
var(y)

stopifnot(all.equal(weighted.var(x, w), var(y)))

hadley/bigvis documentation built on May 17, 2019, 9:45 a.m.

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README.md

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