ewcdf
From spatstat v1.25-5
by Adrian Baddeley
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"
.
See Also
Examples
x <- rnorm(100)
w <- runif(100)
plot(ewcdf(x,w))
Community examples
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