ppm.object

0th

Percentile

Class of Fitted Point Process Models

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

Keywords
spatial
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 maximum pseudolikelihood model fitter, mpl. There are methods print.ppm, predict.ppm and plot.ppm

A ppm object contains at least the following entries: ll{ 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 mpl for explanation of these concepts. The irregular parameters (e.g. the interaction radius of the Strauss process) are encoded in the interaction entry.

See also (for example) Strauss to understand how to specify a point process model with unknown parameters.

Warnings

The internal representation may change in the next few releases of the spatstat package.

mpl, print.ppm, predict.ppm, plot.ppm.

• ppm.object
Examples
library(spatstat)
data(cells)
fit <- mpl(cells, ~ x, Strauss(0.1), correction="periodic")
fit
pred <- predict(fit)
pred <- predict(fit, nx=50, ny=50, type="trend")
plot(fit)
Documentation reproduced from package spatstat, version 1.0-1, License: GPL version 2 or newer

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