# lppm

##### Fit Point Process Model to Point Pattern on Linear Network

Fit a point process model to a point pattern dataset on a linear network

##### Usage

`lppm(X, ...)`

##### Arguments

- X
- Object of class
`"lpp"`

specifying a point pattern on a linear network. - ...
- Arguments passed to
`ppm`

.

##### Details

This function fits a point process model to data that specify
a point pattern on a linear network. It is a counterpart of
the model-fitting function `ppm`

designed
to work with objects of class `"lpp"`

instead of `"ppp"`

.

The argument `X`

should be an object of class `"lpp"`

(created by the command `lpp`

) specifying a point pattern
on a linear network.

The subsequent arguments `...`

will be passed to
`ppm`

. They specify the form of the model.

##### Value

- An object of class
`"lppm"`

representing the fitted model. There are methods for`print`

,`predict`

,`coef`

and similar functions.

##### References

Ang, Q.W. (2010)
*Statistical methodology for events on a network*.
Master's thesis, School of Mathematics and Statistics, University of
Western Australia.
Ang, Q.W., Baddeley, A. and Nair, G. (2012)
Geometrically corrected second-order analysis of
events on a linear network, with applications to
ecology and criminology.
To appear in *Scandinavian Journal of Statistics*.

McSwiggan, G., Nair, M.G. and Baddeley, A. (2012) Fitting Poisson point process models to events on a linear network. Manuscript in preparation.

##### See Also

##### Examples

```
example(lpp)
lppm(X, ~1)
```

*Documentation reproduced from package spatstat, version 1.25-5, License: GPL (>= 2)*