subfits {spatstat.model} | R Documentation |
Extract List of Individual Point Process Models
Description
Takes a Gibbs point process model that has been fitted to several point patterns simultaneously, and produces a list of fitted point process models for the individual point patterns.
Usage
subfits(object, what="models", verbose=FALSE, new.coef=NULL)
subfits.old(object, what="models", verbose=FALSE, new.coef=NULL)
subfits.new(object, what="models", verbose=FALSE)
Arguments
object |
An object of class |
what |
What should be returned.
Either |
verbose |
Logical flag indicating whether to print progress reports. |
new.coef |
Advanced use only. Numeric vector or matrix of coefficients
to replaced the fitted coefficients |
Details
object
is assumed to have been generated by
mppm
. It represents a point process model that has been
fitted to a list of several point patterns, with covariate data.
For each of the individual point pattern
datasets, this function derives the corresponding fitted model
for that dataset only (i.e. a point process model for the i
th
point pattern, that is consistent with object
).
If what="models"
,
the result is a list of point process models (a list of objects of class
"ppm"
), one model for each point pattern dataset in the
original fit.
If what="interactions"
,
the result is a list of fitted interpoint interactions (a list of
objects of class
"fii"
).
Two different algorithms are provided, as
subfits.old
and subfits.new
.
Currently subfits
is the same as the old algorithm
subfits.old
because the newer algorithm is too memory-hungry.
Value
A list of point process models (a list of objects of class
"ppm"
) or a list of fitted interpoint interactions (a list of
objects of class "fii"
).
Author(s)
Adrian Baddeley, Ida-Maria Sintorn and Leanne Bischoff. Implemented in spatstat by Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
References
Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press.
See Also
Examples
H <- hyperframe(Wat=waterstriders)
fit <- mppm(Wat~x, data=H)
subfits(fit)
H$Wat[[3]] <- rthin(H$Wat[[3]], 0.1)
fit2 <- mppm(Wat~x, data=H, random=~1|id)
subfits(fit2)