Weighted quantiles

Functions to compute weighted quantiles and the weighted interquartile range.

Usage

wquantile(wt = rep(1,length(x)), x, probs, already.sorted = FALSE, 
          already.normalized = FALSE)
wIQR(wt = rep(1,length(x)), x, already.sorted = FALSE, 
     already.normalized = FALSE)

Arguments

wt

Vector of weights

x

Vector of data, same length as wt

probs

Numeric vector of probabilities with values in [0,1].

already.sorted

If FALSE, sort wt and x in increasing order of x. If TRUE, it is assumed that wt and x are already sorted.

already.normalized

If FALSE, normalize wt by diving each entry by the sum of all entries. If TRUE, it is assumed that sum(wt)==1

Details

wquantile uses the findInterval function. wIQR calls the wquantile function.

Value

Returns the sample quantiles or interquartile range of a discrete distribution with support points x and corresponding probability masses wt

See also

npEM

Examples

IQR(1:10)
#> [1] 4.5
wIQR(x=1:10) # Note:  Different algorithm than IQR function
#> [1] 5
wIQR(1:10,1:10) # Weighted quartiles are now 4 and 8
#> [1] 4