# rpoislpp: Poisson Point Process on a Linear Network In spatstat.linnet: Linear Networks Functionality of the 'spatstat' Family

 rpoislpp R Documentation

## Poisson Point Process on a Linear Network

### Description

Generates a realisation of the Poisson point process with specified intensity on the given linear network.

### Usage

```rpoislpp(lambda, L, ..., nsim=1, drop=TRUE)
```

### Arguments

 `lambda` Intensity of the Poisson process. A single number, a `function(x,y)`, a pixel image (object of class `"im"`), or a vector of numbers, a list of functions, or a list of images. `L` A linear network (object of class `"linnet"`, see `linnet`). Can be omitted in some cases: see Details. `...` Arguments passed to `rpoisppOnLines`. `nsim` Number of simulated realisations to generate. `drop` Logical value indicating what to do when `nsim=1`. If `drop=TRUE` (the default), the result is a point pattern. If `drop=FALSE`, the result is a list with one entry which is a point pattern.

### Details

This function uses `rpoisppOnLines` to generate the random points.

Argument `L` can be omitted, and defaults to `as.linnet(lambda)`, when `lambda` is a function on a linear network (class `"linfun"`) or a pixel image on a linear network (`"linim"`).

### Value

If `nsim = 1` and `drop=TRUE`, a point pattern on the linear network, i.e.\ an object of class `"lpp"`. Otherwise, a list of such point patterns.

### Author(s)

\wei

`runiflpp`, `rlpp`, `lpp`, `linnet`

### Examples

```   X <- rpoislpp(5, simplenet)
plot(X)
# multitype
X <- rpoislpp(c(a=5, b=5), simplenet)
```

spatstat.linnet documentation built on Nov. 16, 2022, 1:09 a.m.