quantile.ewcdf: Quantiles of Weighted Empirical Cumulative Distribution...

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

Quantiles of Weighted Empirical Cumulative Distribution Function

Description

Compute quantiles of a weighted empirical cumulative distribution function.

Usage

  ## S3 method for class 'ewcdf'
quantile(x, probs = seq(0, 1, 0.25),
                 names = TRUE, ...,
                 normalise = TRUE, type=1)

Arguments

x	A weighted empirical cumulative distribution function (object of class "ewcdf", produced by ewcdf) for which the quantiles are desired.
probs	probabilities for which the quantiles are desired. A numeric vector of values between 0 and 1.
names	Logical. If TRUE, the resulting vector of quantiles is annotated with names corresponding to probs.
...	Ignored.
normalise	Logical value indicating whether x should first be normalised so that it ranges between 0 and 1.
type	Integer specifying the type of quantile to be calculated, as explained in quantile.default. Only types 1, 2 and 4 are currently implemented.

Details

This is a method for the generic quantile function for the class ewcdf of empirical weighted cumulative distribution functions.

The quantile for a probability p is computed as the right-continuous inverse of the cumulative distribution function x (assuming type=1, the default).

If normalise=TRUE (the default), the weighted cumulative function x is first normalised to have total mass 1 so that it can be interpreted as a cumulative probability distribution function.

Value

Numeric vector of quantiles, of the same length as probs.

Author(s)

\spatstatAuthors

and Kevin Ummel.

See Also

ewcdf, quantile

Examples

  z <- rnorm(50)
  w <- runif(50)
  Fun <- ewcdf(z, w)
  quantile(Fun, c(0.95,0.99))

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