mean.ewcdf: Mean of Empirical Cumulative Distribution Function

In spatstat.univar: One-Dimensional Probability Distribution Support for the 'spatstat' Family

Mean of Empirical Cumulative Distribution Function

Description

Calculates the mean of a (weighted or unweighted) empirical cumulative distribution function.

Usage

## S3 method for class 'ecdf'
mean(x, trim=0, ...)

## S3 method for class 'ewcdf'
mean(x, trim=0, ...)

Arguments

x	An empirical cumulative distribution function (object of class "ecdf" created by ecdf) or a weighted empirical cumulative distribution function (object of class "ewcdf" created by ewcdf).
trim	The fraction (0 to 0.5) of data values to be trimmed from each end of their range, before the mean is computed.
...	Ignored.

Details

These functions are methods for the generic mean for the classes "ecdf" and "ewcdf".

They calculate the mean of the probability distribution corresponding to the cumulative distribution function x. This is equivalent to calculating the (weighted or unweighted) mean of the original data values.

For weighted empirical cumulative distribution functions (class "ewcdf") the weights will first be normalised so that they sum to 1. The result of mean.ewcdf is always an average or weighted average or the original data values. The argument trim is interpreted as a probability under this normalised distribution; the corresponding quantiles are computed, and data outside these quantiles is deleted before calculating the weighted mean.

Value

A single number.

Author(s)

\spatstatAuthors

.

See Also

Generic mean and weighted.mean.

ecdf, ewcdf to create the cumulative distribution functions.

stieltjes for integration with respect to a cumulative distribution function.

Examples

  x <- 1:5
  mean(x)
  mean(ecdf(x))
  w <- 1:5
  mean(ewcdf(x, w))

spatstat.univar documentation built on June 8, 2025, 12:52 p.m.