fitted.ppm {spatstat} | R Documentation |
Given a point process model fitted to a point pattern, compute the fitted conditional intensity of the model at the points of the quadrature scheme used to fit the model.
fitted.ppm(object, ...)
object |
The fitted point process model (an object of class "ppm" )
|
... |
Ignored. |
The argument object
must be a fitted point process model
(object of class "ppm"
). Such objects are produced by the maximum
pseudolikelihood fitting algorithm mpl
).
This function evaluates the conditional intensity
lambdahat(u,x) of the fitted point process
model for certain locations u,
where x
is the original point pattern dataset to which
the model was fitted.
The locations u at which the fitted conditional intensity
is evaluated, are the points of the
quadrature scheme used to fit the model in mpl
.
They include the data points (the points of the original point pattern
dataset x
) and other ``dummy'' points
in the window of observation.
Use predict.ppm
to compute the fitted conditional
intensity at other locations or with other values of the
explanatory variables.
A vector containing the values of the fitted conditional intensity.
Entries in this vector correspond to the quadrature points (data or
dummy points) used to fit the model. The quadrature points can be
extracted from object
by union.quad(quad.ppm(object))
.
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf
Baddeley, A., Moller, J. and Turner, R. (2004) Residuals for spatial point processes. In preparation.
require(spatstat) data(cells) str <- mpl(cells, ~x, Strauss(r=0.15), rbord=0.15) lambda <- fitted(str) # extract quadrature points in corresponding order quadpoints <- union.quad(quad.ppm(str)) # plot conditional intensity values # as circles centred on the quadrature points quadmarked <- setmarks(quadpoints, lambda) plot(quadmarked)