ppm.object: Class of Fitted Point Process Models

In spatstat.model: Parametric Statistical Modelling and Inference for the 'spatstat' Family

Class of Fitted Point Process Models

Description

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

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
nobs	nobs.ppm	number of observations

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
add1	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
unitname	unitname.ppm	Name of unit of length

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

Author(s)

\adrian

and \rolf.

See Also

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

Examples

  fit <- ppm(cells ~ x, Strauss(0.1), correction="periodic")
  fit
  coef(fit)
  
    pred <- predict(fit)
  
  pred <- predict(fit, ngrid=20, type="trend")
  if(interactive()) {
  plot(fit)
  }  

spatstat.model documentation built on Sept. 30, 2024, 9:26 a.m.