| 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 ith
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)