# quantile.ewcdf

0th

Percentile

##### Quantiles of Weighted Empirical Cumulative Distribution Function

Compute quantiles of a weighted empirical cumulative distribution function.

Keywords
spatial, nonparametric
##### Usage
# S3 method for 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.

ewcdf, quantile

##### Aliases
• quantile.ewcdf
##### Examples
# NOT RUN {
z <- rnorm(50)
w <- runif(50)
Fun <- ewcdf(z, w)
quantile(Fun, c(0.95,0.99))
# }

Documentation reproduced from package spatstat, version 1.55-1, License: GPL (>= 2)

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