model.frame.lppm {spatstat.linnet} | R Documentation |
Extract the Variables in a Point Process Model on a Network
Description
Given a fitted point process model on a network, this function returns a data frame containing all the variables needed to fit the model using the Berman-Turner device.
Usage
## S3 method for class 'lppm'
model.frame(formula, ...)
Arguments
formula |
A fitted point process model on a linear network.
An object of class |
... |
Additional arguments passed to |
Details
The function model.frame
is generic.
This function is a method for model.frame
for fitted point process models
on a linear network (objects of class "lppm"
).
The first argument should be a fitted point process model;
it has to be named formula
for consistency with the generic
function.
The result is a data frame containing all the variables used in
fitting the model. The data frame has one row for each quadrature point
used in fitting the model. The quadrature scheme can be extracted using
quad.ppm
.
Value
A data.frame
containing all the variables used in the
fitted model, plus additional variables specified in ...
.
It has an additional attribute "terms"
containing information
about the model formula. For details see model.frame.glm
.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
References
Baddeley, A. and Turner, R. (2000) Practical maximum pseudolikelihood for spatial point patterns. Australian and New Zealand Journal of Statistics 42, 283–322.
See Also
lppm
,
model.frame
,
model.matrix.ppm
Examples
fit <- lppm(spiders ~ x)
mf <- model.frame(fit)