matrixStats (version 0.53.0)

weightedMean: Weighted Arithmetic Mean

Description

Computes the weighted sample mean of a numeric vector.

Usage

weightedMean(x, w = NULL, idxs = NULL, na.rm = FALSE, refine = FALSE,
  ...)

Arguments

x

a numeric vector containing the values whose weighted mean is to be computed.

w

a vector of weights the same length as x giving the weights to use for each element of x. Negative weights are treated as zero weights. Default value is equal weight to all values.

idxs

A vector indicating subset of elements to operate over. If NULL, no subsetting is done.

na.rm

a logical value indicating whether NA values in x should be stripped before the computation proceeds, or not. If NA, no check at all for NAs is done. Default value is NA (for efficiency).

refine

If TRUE and x is numeric, then extra effort is used to calculate the average with greater numerical precision, otherwise not.

...

Not used.

Value

Returns a numeric scalar. If x is of zero length, then NaN is returned, which is consistent with mean().

Missing values

This function handles missing values consistently weighted.mean. More precisely, if na.rm = FALSE, then any missing values in either x or w will give result NA_real_. If na.rm = TRUE, then all (x, w) data points for which x is missing are skipped. Note that if both x and w are missing for a data points, then it is also skipped (by the same rule). However, if only w is missing, then the final results will always be NA_real_ regardless of na.rm.

See Also

mean() and weighted.mean.

Examples

# NOT RUN {
x <- 1:10
n <- length(x)

w <- rep(1, times = n)
m0 <- weighted.mean(x, w)
m1 <- weightedMean(x, w)
stopifnot(identical(m1, m0))

# Pull the mean towards zero
w[1] <- 5
m0 <- weighted.mean(x, w)
m1 <- weightedMean(x, w)
stopifnot(identical(m1, m0))

# Put even more weight on the zero
w[1] <- 8.5
m0 <- weighted.mean(x, w)
m1 <- weightedMean(x, w)
stopifnot(identical(m1, m0))

# All weight on the first value
w[1] <- Inf
m0 <- weighted.mean(x, w)
m1 <- weightedMean(x, w)
stopifnot(identical(m1, m0))

# All weight on the last value
w[1] <- 1
w[n] <- Inf
m0 <- weighted.mean(x, w)
m1 <- weightedMean(x, w)
stopifnot(identical(m1, m0))

# All weights set to zero
w <- rep(0, times = n)
m0 <- weighted.mean(x, w)
m1 <- weightedMean(x, w)
stopifnot(identical(m1, m0))
# }