A variation of ecdf() that can be applied to weighted samples.
Arguments
- x
numeric vector: sample values
- weights
Weights for the sample. One of:
numeric vector of same length as
x: weights for corresponding values inx, which will be normalized to sum to 1.NULL: indicates no weights are provided, so the unweighted empirical cumulative distribution function (equivalent toecdf()) is returned.
- na.rm
logical: if
TRUE, corresponding entries inxandweightsare removed if either isNA.
Value
weighted_ecdf() returns a function of class "weighted_ecdf", which also
inherits from the stepfun() class. Thus, it also has plot() and print()
methods. Like ecdf(), weighted_ecdf() also provides a quantile() method,
which dispatches to weighted_quantile().
Details
Generates a weighted empirical cumulative distribution function, \(F(x)\).
Given \(x\), a sorted vector (derived from x), and \(w_i\), the corresponding
weight for \(x_i\), \(F(x)\) is a step function with steps at each \(x_i\)
with \(F(x_i)\) equal to the sum of all weights up to and including \(w_i\).
