Given a point process model that has been fitted to spatial point pattern data on a linear network, this function extracts the design matrix of the model.
# S3 method for lppm
model.matrix(object,
data=model.frame(object, na.action=NULL),
...,
keepNA=TRUE)
A matrix. Columns of the matrix are canonical covariates in the model.
Rows of the matrix correspond to quadrature points
in the fitting procedure (provided keepNA=TRUE
).
The fitted point process model. An object of class "lppm"
.
A model frame, containing the data required for the Berman-Turner device.
Logical. Determines whether rows containing NA values will be deleted or retained.
Other arguments (such as na.action
) passed to
model.matrix.lm
.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
This is a method for the generic function
model.matrix
.
It extracts the design matrix of a spatial point process model
on a linear network (object of class "lppm"
).
More precisely, this command extracts the design matrix of the generalised linear model associated with a spatial point process model.
The object
must be a fitted point process model
on a network (object of class "lppm"
)
produced by the model-fitting function lppm
.
The method model.matrix.lppm
extracts the model matrix for the GLM.
The result is a matrix, with one row for every quadrature point in the fitting procedure, and one column for every canonical covariate in the design matrix.
If there are NA
values in the covariates,
the argument keepNA
determines whether to retain or delete
the corresponding rows of the model matrix. The default
keepNA=TRUE
is to retain them. Note that this differs from
the default behaviour of many other methods for model.matrix
,
which typically delete rows containing NA
.
model.matrix
,
model.images.lppm
,
lppm
fit <- lppm(spiders ~ x + y)
head(model.matrix(fit))
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