ppm.object
Class of Fitted Point Process Models
A class ppm
to represent a fitted stochastic model
for a point process. The output of ppm
.
- 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 model fitter,
ppm
.
There are methods print.ppm
,
plot.ppm
, predict.ppm
, fitted.ppm
and coef.ppm
for the generic functions
print
, plot
, predict
,
fitted
and coef
respectively.
See also (for example) Strauss
to understand how to specify
a point process model with unknown parameters.
Information about the data (to which the model was fitted)
can be extracted using data.ppm
, dummy.ppm
and quad.ppm
.
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 may change in the next few releases
of the
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)
pred <- predict(fit)
pred <- predict(fit, ngrid=20, type="trend")
plot(fit)