Given a point process model that has been fitted to spatial point pattern data, this function extracts the design matrix of the model.

```
# S3 method for ppm
model.matrix(object,
data=model.frame(object, na.action=NULL),
…,
Q=NULL, keepNA=TRUE)
``` # S3 method for kppm
model.matrix(object,
data=model.frame(object, na.action=NULL),
…,
Q=NULL, keepNA=TRUE)

# S3 method for dppm
model.matrix(object,
data=model.frame(object, na.action=NULL),
…,
Q=NULL, keepNA=TRUE)

# S3 method for ippm
model.matrix(object,
data=model.frame(object, na.action=NULL),
…,
Q=NULL, keepNA=TRUE,
irregular=FALSE)

object

The fitted point process model. An object of class `"ppm"`

or `"kppm"`

or `"dppm"`

or `"ippm"`

.

data

A model frame, containing the data required for the Berman-Turner device.

Q

A point pattern (class `"ppp"`

) or quadrature scheme
(class `"quad"`

) specifying new locations where the
covariates should be computed.

keepNA

Logical. Determines whether rows containing NA values will be deleted or retained.

…

Other arguments (such as `na.action`

) passed to
`model.matrix.lm`

.

irregular

Logical value indicating whether to include the irregular score components.

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`

).

These commands are methods for the generic function
`model.matrix`

.
They extract the design matrix of a spatial point process model
(class `"ppm"`

or `"kppm"`

or `"dppm"`

).

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
(object of class `"ppm"`

or `"kppm"`

or `"dppm"`

)
fitted to spatial point pattern data.
Such objects are produced by the model-fitting
functions `ppm`

, `kppm`

,
and `dppm`

.

The methods `model.matrix.ppm`

,
`model.matrix.kppm`

,
and `model.matrix.dppm`

extract 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 constructed 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`

.

The quadrature points themselves can be extracted using
`quad.ppm`

.

`model.matrix`

,
`model.images`

,
`ppm`

,
`kppm`

,
`dppm`

,
`ippm`

,
`ppm.object`

,
`quad.ppm`

,
`residuals.ppm`

# NOT RUN { fit <- ppm(cells ~ x) head(model.matrix(fit)) model.matrix(fit, Q=runifpoint(5)) kfit <- kppm(redwood ~ x, "Thomas") m <- model.matrix(kfit) # }