weightedMad: Weighted Median Absolute Deviation (MAD)
In matrixStats: Methods that apply to rows and columns of a matrix

Description Usage Arguments Value Missing values Author(s) See Also Examples

Computes a weighted MAD of a numeric vector.

1 2	## Default S3 method: weightedMad(x, w, na.rm=FALSE, constant=1.4826, center=NULL, ...)

`x`	a `numeric` `vector` containing the values whose weighted MAD 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.
`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 `NA`s is done. Default value is `NA` (for effiency).
`constant`	A `numeric` scale factor, cf. `mad`.
`center`	Optional `numeric` scalar specifying the center location of the data. If `NULL`, it is estimated from data.
`...`	Not used.

Returns a numeric scalar.

Missing values are dropped at the very beginning, if argument na.rm is TRUE, otherwise not.

Henrik Bengtsson

For the non-weighted MAD, see mad. Internally weightedMedian() is used to calculate the weighted median.

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

m1 <- mad(x)
m2 <- weightedMad(x)
stopifnot(identical(m1, m2))

w <- rep(1, times=n)
m1 <- weightedMad(x, w)
stopifnot(identical(m1,m2))

# All weight on the first value
w[1] <- Inf
m <- weightedMad(x, w)
stopifnot(m == 0)

# All weight on the first two values
w[1:2] <- Inf
m1 <- mad(x[1:2])
m2 <- weightedMad(x, w)
stopifnot(identical(m1,m2))

# All weights set to zero
w <- rep(0, times=n)
m <- weightedMad(x, w)
stopifnot(is.na(m))