# ewcdf

0th

Percentile

##### Weighted Empirical Cumulative Distribution Function

Compute a weighted version of the empirical cumulative distribution function.

Keywords
nonparametric, univar
##### Usage
ewcdf(x, weights = rep(1/length(x), length(x)))
##### Arguments
x
Numeric vector of observations.
weights
Numeric vector of non-negative weights for x.
##### Details

This is a modification of the standard function ecdf allowing the observations x to have weights.

The weighted e.c.d.f. (empirical cumulative distribution function) Fn is defined so that, for any real number y, the value of Fn(y) is equal to the total weight of all entries of x that are less than or equal to y. That is Fn(y) = sum(weights[x <= y])<="" code="">.

Thus Fn is a step function which jumps at the values of x. The height of the jump at a point y is the total weight of all entries in x number of tied observations at that value. Missing values are ignored.

If weights is omitted, the default is equivalent to ecdf(x).

##### Value

• A function, of class "ecdf", inheriting from "stepfun".

ecdf

• ewcdf
##### Examples
x <- rnorm(100)
w <- runif(100)
plot(ewcdf(x,w))
Documentation reproduced from package spatstat, version 1.12-5, License: GPL (>= 2)

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