quad.ppm(object, drop=FALSE)"ppm")."quad")."ppm" represents a point process model
that has been fitted to data. It is typically produced by
the model-fitting algorithm ppm.
The maximum pseudolikelihood algorithm in ppm
approximates the pseudolikelihood
integral by a sum over a finite set of quadrature points,
which is constructed by augmenting
the original data point pattern by a set of ``dummy'' points.
The fitted model object returned by ppm
contains complete information about this quadrature scheme.
See ppm or ppm.object for further
information.
This function quad.ppm extracts the quadrature scheme.
A typical use of this function would be to inspect the quadrature scheme
(points and weights) to gauge the accuracy of the approximation to the
exact pseudolikelihood. It may happen that some quadrature points are not actually used in
fitting the model (typically because the value of a covariate is NA
at these points). The argument drop specifies whether these
unused quadrature points shall be deleted (drop=TRUE) or
retained (drop=FALSE) in the return value.
See ppm.object for a list of all operations that can be
performed on objects of class "ppm".
See quad.object for a list of all operations that can be
performed on objects of class "quad".
ppm.object,
quad.object,
ppmdata(cells)
fit <- ppm(cells, ~1, Strauss(r=0.1))
Q <- quad.ppm(fit)
plot(Q)
Q$data$n
Q$dummy$nRun the code above in your browser using DataLab