spatstat (version 1.48-0)

ppm.object: Class of Fitted Point Process Models

Description

A class ppm to represent a fitted stochastic model for a point process. The output of ppm.

Internal format

If you really need to get at the internals, a ppm object contains at least the following entries:

coef

the fitted regular parameters (as returned by glm)

trend

the trend formula or NULL

interaction

the point process interaction family (an object of class "interact") or NULL

Q

the quadrature scheme used

maxlogpl

the maximised value of log pseudolikelihood

correction

name of edge correction method used

See ppm for explanation of these concepts. The irregular parameters (e.g. the interaction radius of the Strauss process) are encoded in the interaction entry. However see the Warnings.

Warnings

The internal representation of ppm objects may change slightly between releases of the spatstat package.

Details

An object of class ppm represents a stochastic point process model that has been fitted to a point pattern dataset. Typically it is the output of the model fitter, ppm.

The class ppm has methods for the following standard generic functions:

generic	method
description	print
print.ppm	print details
plot	plot.ppm
plot fitted model	predict
predict.ppm	fitted intensity and conditional intensity
fitted	fitted.ppm
fitted intensity	coef
coef.ppm	fitted coefficients of model
anova	anova.ppm
Analysis of Deviance	formula
formula.ppm	Extract model formula
terms	terms.ppm
Terms in the model formula	labels
labels.ppm	Names of estimable terms in the model formula
residuals	residuals.ppm
Point process residuals	simulate
simulate.ppm	Simulate the fitted model
update	update.ppm
Change or refit the model	vcov
vcov.ppm	Variance/covariance matrix of parameter estimates
model.frame	model.frame.ppm
Model frame	model.matrix
model.matrix.ppm	Design matrix
logLik	logLik.ppm
log pseudo likelihood	extractAIC
extractAIC.ppm	pseudolikelihood counterpart of AIC

Objects of class ppm can also be handled by the following standard functions, without requiring a special method:

name

description

confint

Confidence intervals for parameters

step

Stepwise model selection

drop1

One-step model improvement

The class ppm also has methods for the following generic functions defined in the spatstat package:

generic	method
description	as.interact
as.interact.ppm	Interpoint interaction structure
as.owin	as.owin.ppm
Observation window of data	berman.test
berman.test.ppm	Berman's test
envelope	envelope.ppm
Simulation envelopes	fitin
fitin.ppm	Fitted interaction
is.marked	is.marked.ppm
Determine whether the model is marked	is.multitype
is.multitype.ppm	Determine whether the model is multitype
is.poisson	is.poisson.ppm
Determine whether the model is Poisson	is.stationary
is.stationary.ppm	Determine whether the model is stationary
cdf.test	cdf.test.ppm
Spatial distribution test	quadrat.test
quadrat.test.ppm	Quadrat counting test
reach	reach.ppm
Interaction range of model	rmhmodel
rmhmodel.ppm	Model in a form that can be simulated
rmh	rmh.ppm
Perform simulation	generic

Information about the data (to which the model was fitted) can be extracted using data.ppm, dummy.ppm and quad.ppm.

See Also

ppm, coef.ppm, fitted.ppm, print.ppm, predict.ppm, plot.ppm.

Examples

  data(cells)
  fit <- ppm(cells, ~ x, Strauss(0.1), correction="periodic")
  fit
  coef(fit)
  ## Not run: 
#   pred <- predict(fit)
#   ## End(Not run)
  pred <- predict(fit, ngrid=20, type="trend")
  ## Not run: 
#   plot(fit)
#   ## End(Not run)