# quad.ppm

##### Extract Quadrature Scheme Used to Fit a Point Process Model

Given a fitted point process model, this function extracts the quadrature scheme used to fit the model.

##### Usage

`quad.ppm(object, drop=FALSE)`

##### Arguments

- object
- fitted point process model (an object of class
`"ppm"`

). - drop
- Logical value determining whether to delete quadrature points that were not used to fit the model.

##### Details

An object of class `"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"`

.

##### Value

- A quadrature scheme (object of class
`"quad"`

).

##### See Also

##### Examples

```
data(cells)
fit <- ppm(cells, ~1, Strauss(r=0.1))
Q <- quad.ppm(fit)
plot(Q)
Q$data$n
Q$dummy$n
```

*Documentation reproduced from package spatstat, version 1.18-1, License: GPL (>= 2)*