# quantile.ewcdf: Quantiles of Weighted Empirical Cumulative Distribution... In spatstat.geom: Geometrical Functionality of the 'spatstat' Family

## Description

Compute quantiles of a weighted empirical cumulative distribution function.

## Usage

 ```1 2 3 4``` ``` ## 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 and 2 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`.

\spatstatAuthors

and Kevin Ummel.

## See Also

`ewcdf`, `quantile`

## Examples

 ```1 2 3 4``` ``` z <- rnorm(50) w <- runif(50) Fun <- ewcdf(z, w) quantile(Fun, c(0.95,0.99)) ```

spatstat.geom documentation built on April 15, 2021, 9:06 a.m.