# residuals.ppm

##### Residuals for Fitted Point Process Model

Given a point process model fitted to a point pattern, compute residuals.

##### Usage

```
## S3 method for class 'ppm':
residuals(object, type="raw", \dots)
```

##### Arguments

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

) for which residuals should be calculated. - type
- String indicating the type of residuals to be calculated.
Current options are
`"raw"`

,`"inverse"`

and`"pearson"`

. A partial match is adequate. - ...
- Ignored.

##### Details

This function computes several kinds of residuals for the fit of
a point process model to a spatial point pattern dataset
(Baddeley et al, 2005).
Use `diagnose.ppm`

to produce diagnostic plots
based on these residuals.

The argument `object`

must be a fitted point process model
(object of class `"ppm"`

). Such objects are produced by the maximum
pseudolikelihood fitting algorithm `ppm`

).
This fitted model object contains complete
information about the original data pattern.

Residuals are attached both to the data points and to some
other points in the window of observation (namely, to the dummy
points of the quadrature scheme used to fit the model).
If the fitted model is correct, then the sum of the
residuals over all (data and dummy) points in a spatial region $B$
has mean zero. For further explanation, see Baddeley et al (2005).
The type of residual
is chosen by the argument `type`

. Current options are

[object Object],[object Object],[object Object]

Use `diagnose.ppm`

to produce diagnostic plots
based on these residuals.

##### Value

- A vector containing the (discretised) residuals.
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))`

.

##### synopsis

## S3 method for class 'ppm': residuals(object, type="raw", \dots, fittedvalues=fitted.ppm(object))

##### References

Baddeley, A., Turner, R., Moller, J. and Hazelton, M. (2005)
Residual analysis for spatial point processes.
*Journal of the Royal Statistical Society, Series B*
**67**, 617--666.

##### See Also

##### Examples

```
data(cells)
fit <- ppm(cells, ~x, Strauss(r=0.15), rbord=0.15)
rp <- residuals.ppm(fit, type="pe")
sum(rp) # should be close to 0
# extract quadrature points to which the residuals correspond
quadpoints <- union.quad(quad.ppm(fit))
# plot residuals as marks attached to the quadrature points
quadmarked <- setmarks(quadpoints, rp)
plot(quadmarked)
```

*Documentation reproduced from package spatstat, version 1.9-1, License: GPL version 2 or newer*