edf: Empirical cummulative distribution function

In asymmetry.measures: Asymmetry Measures for Probability Density Functions

Description

Empirical (nonparametric) cummulative distribution function for given a random sample.

Usage

 edf(xin, xout) 

Arguments

xin	A vector of data points - the available sample.
xout	A vector of design points where the distribution function will be estimated.

Details

The empirical distribution function estimator at x is defined as the number of observations up to x, divided by n, i.e.

F_{n}(x) = \frac{\# \{ X_{1},..,X_{n}\} ≤ x}{n}

.

Value

A vector with the estimated distribution function at xout.

Author(s)

Dimitrios Bagkavos and Lucia Gamez Gallardo

R implementation and documentation:

Dimitrios Bagkavos <[e-mail]> , Lucia Gamez Gallardo <[e-mail]>

References

Hollander, M. abd Wolfe, D.A. (1999), Nonparametric Statistical Methods, 2nd edition, Wiley.

Examples

x.in <- rexp(200)
x.out <- seq(0.1,5,length=60)
dist.est <- edf(x.in,x.out)
plot(x.out,dist.est,col="blue",main="Empirical c.d.f.",xlab="x",yla ="probability")

asymmetry.measures documentation built on July 22, 2020, 9:06 a.m.