# rSwitzerlpp

##### Switzer-type Point Process on Linear Network

Generate a realisation of the Switzer-type point process on a linear network.

##### Usage

```
rSwitzerlpp(L, lambdacut, rintens = rexp, …,
cuts=c("points", "lines"))
```

##### Arguments

- L
Linear network (object of class

`"linnet"`

).- lambdacut
Intensity of Poisson process of breakpoints.

- rintens
Optional. Random variable generator used to generate the random intensity in each component.

- …
Additional arguments to

`rintens`

.- cuts
String (partially matched) specifying the type of random cuts to be generated.

##### Details

This function generates simulated realisations of the Switzer-type point process on a network, as described in Baddeley et al (2017).

The linear network is first divided into pieces by a random mechanism:

if

`cuts="points"`

, a Poisson process of breakpoints with intensity`lambdacut`

is generated on the network, and these breakpoints separate the network into connected pieces.if

`cuts="lines"`

, a Poisson line process in the plane with intensity`lambdacut`

is generated; these lines divide space into tiles; the network is divided into subsets associated with the tiles. Each subset may not be a connected sub-network.

In each piece of the network, a random intensity is generated
using the random variable generator `rintens`

(the default is
a negative exponential random variable with rate 1). Given the
intensity value, a Poisson process is generated with the specified
intensity.

The intensity of the final process is determined by the mean
of the values generated by `rintens`

. If `rintens=rexp`

(the
default), then the parameter `rate`

specifies the inverse of the
intensity.

##### Value

Point pattern on a linear network (object of class `"lpp"`

)
with an attribute `"breaks"`

containing the breakpoints (if
`cuts="points"`

) or the random lines (if `cuts="lines"`

).

##### References

Baddeley, A., Nair, G., Rakshit, S. and McSwiggan, G. (2017)
‘Stationary’ point processes are uncommon on
linear networks. *STAT* **6**, 68--78.

##### See Also

##### Examples

```
# NOT RUN {
plot(rSwitzerlpp(domain(spiders), 0.01, rate=100))
plot(rSwitzerlpp(domain(spiders), 0.0005, rate=100, cuts="l"))
# }
```

*Documentation reproduced from package spatstat, version 1.63-0, License: GPL (>= 2)*