spatstat (version 1.34-1)

lppm: Fit Point Process Model to Point Pattern on Linear Network

Description

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

Usage

lppm(X, ..., eps=NULL, nd=1000)

Arguments

X

Object of class "lpp" specifying a point pattern on a linear network.

...

Arguments passed to ppm.

eps

Optional. Spacing between dummy points along each segment of the network.

nd

Optional. Number of dummy points equally spaced along each segment of the network. Ignored if eps is given.

Value

• An object of class "lppm" representing the fitted model. There are methods for print, predict, coef and similar functions.

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.

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

methods.lppm, predict.lppm, ppm, lpp.

Examples

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