Given a point process model fitted to multiple point patterns, compute residuals for each pattern.

```
# S3 method for mppm
residuals(object, type = "raw", ...,
fittedvalues = fitted.mppm(object))
```

object

Fitted point process model (object of class `"mppm"`

).

…

Ignored.

type

Type of residuals: either `"raw"`

, `"pearson"`

or `"inverse"`

. Partially matched.

fittedvalues

Advanced use only. Fitted values of the model to be used in the calculation.

A list of signed measures (objects of class `"msr"`

)
giving the residual measure for each of the original point patterns.
See Details.

Baddeley et al (2005) defined residuals for the fit of
a point process model to spatial point pattern data.
For an explanation of these residuals, see the help file for
`residuals.ppm`

.

This function computes the residuals
for a point process model fitted to *multiple* point patterns.
The `object`

should be an object of class `"mppm"`

obtained
from `mppm`

.

The return value is a list.
The number of entries in the list equals the
number of point patterns in the original data. Each entry in the list
has the same format as the output of
`residuals.ppm`

.
That is, each entry in the list is a signed measure (object of
class `"msr"`

) giving the residual measure for the corresponding
point pattern.

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.

Baddeley, A., Rubak, E. and Turner, R. (2015)
*Spatial Point Patterns: Methodology and Applications with R*.
London: Chapman and Hall/CRC Press.

# NOT RUN { fit <- mppm(Bugs ~ x, hyperframe(Bugs=waterstriders)) r <- residuals(fit) # compute total residual for each point pattern rtot <- sapply(r, integral.msr) # standardise the total residuals areas <- sapply(windows.mppm(fit), area.owin) rtot/sqrt(areas) # }