summary method for class "kppm".
# S3 method for kppm
summary(object, …, quick=FALSE) # S3 method for summary.kppm
print(x, …)
A fitted Cox or cluster point process model (object of
class "kppm").
Logical value controlling the scope of the summary.
Arguments passed to summary.ppm or
print.summary.ppm controlling the treatment of
the trend component of the model.
Object of class "summary.kppm" as returned by
summary.kppm.
summary.kppm returns an object of class "summary.kppm",
while print.summary.kppm returns NULL.
The result of summary.kppm includes at least the
following components:
character string name of the original point pattern data
logical value indicating whether the model is stationary
the clusters argument to kppm
character string describing the model
TRUE if the model is a Poisson cluster process,
FALSE if it is a log-Gaussian Cox process
Estimated intensity: numeric value, or pixel image
Mean cluster size: numeric value, pixel image, or
NULL
list of fitted parameters for the cluster model
list of fixed parameters for the cluster model, if any
character string representing the original call to
kppm
This is a method for the generic summary
for the class "kppm". An object of class "kppm"
describes a fitted Cox or cluster point process model.
See kppm.
summary.kppm extracts information about the
type of model that has been fitted, the data to which the model was
fitted, and the values of the fitted coefficients.
print.summary.kppm prints this information in a
comprehensible format.
In normal usage, print.summary.kppm is invoked implicitly
when the user calls summary.kppm without assigning its value
to anything. See the examples.
You can also type coef(summary(object)) to extract a table
of the fitted coefficients of the point process model object
together with standard errors and confidence limits.
# NOT RUN {
fit <- kppm(redwood ~ 1, "Thomas")
summary(fit)
coef(summary(fit))
# }
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