fitted.ppm
Fitted Conditional Intensity for Point Process Model
Given a point process model fitted to a point pattern, compute the fitted conditional intensity of the model at the points of the pattern, or at the points of the quadrature scheme used to fit the model.
Usage
## S3 method for class 'ppm':
fitted(object, \dots, type="lambda", dataonly=FALSE,
drop=FALSE, check=TRUE, repair=TRUE)
Arguments
- object
- The fitted point process model (an object of class
"ppm"
) - ...
- Ignored.
- type
- String (partially matched) indicating whether the fitted value is the
conditional intensity (
"lambda"
) or the trend ("trend"
). - dataonly
- Logical. If
TRUE
, then values will only be computed at the points of the data point pattern. IfFALSE
, then values will be computed at all the points of the quadrature scheme used to fit the model, including the point - drop
- Logical value determining whether to delete quadrature points that were not used to fit the model.
- check
- Logical value indicating whether to check the internal format
of
object
. If there is any possibility that this object has been restored from a dump file, or has otherwise lost track of the environment where it was originally compu - repair
- Logical value indicating whether to repair the internal format
of
object
, if it is found to be damaged.
Details
The argument object
must be a fitted point process model
(object of class "ppm"
). Such objects are produced by the
model-fitting algorithm ppm
).
This function evaluates the conditional intensity
$\hat\lambda(u, x)$
or spatial trend $\hat b(u)$ 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/trend
is evaluated, are the points of the
quadrature scheme used to fit the model in ppm
.
They include the data points (the points of the original point pattern
dataset x
) and other ``dummy'' points
in the window of observation.
The argument drop
is explained in quad.ppm
.
Use predict.ppm
to compute the fitted conditional
intensity at other locations or with other values of the
explanatory variables.
Value
- A vector containing the values of the fitted conditional intensity
or (if
type="trend"
) the fitted spatial trend. Entries in this vector correspond to the quadrature points (data or dummy points) used to fit the model. The quadrature points can be extracted fromobject
byunion.quad(quad.ppm(object))
.
References
Baddeley, A., Turner, R., Moller, J. and Hazelton, M. (2005). Residual analysis for spatial point processes (with discussion). Journal of the Royal Statistical Society, Series B 67, 617--666.
See Also
Examples
data(cells)
str <- ppm(cells, ~x, Strauss(r=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)