# quantile.ewcdf

##### 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`

.

##### See Also

##### 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 1.57-1, License: GPL (>= 2)*