# plot.mppm

##### plot a Fitted Multiple Point Process Model

Given a point process model fitted to multiple point patterns
by `mppm`

,
compute spatial trend or conditional intensity surface of the model,
in a form suitable for plotting, and (optionally) plot this
surface.

##### Usage

```
# S3 method for mppm
plot(x, …,
trend=TRUE, cif=FALSE, se=FALSE,
how=c("image", "contour", "persp"))
```

##### Arguments

- x
A point process model fitted to multiple point patterns, typically obtained from the model-fitting algorithm

`mppm`

. An object of class`"mppm"`

.- …
Arguments passed to

`plot.ppm`

or`plot.anylist`

controlling the plot.- trend
Logical value indicating whether to plot the fitted trend.

- cif
Logical value indicating whether to plot the fitted conditional intensity.

- se
Logical value indicating whether to plot the standard error of the fitted trend.

- how
Single character string indicating the style of plot to be performed.

##### Details

This is the `plot`

method for the class `"mppm"`

of point process models fitted to multiple point patterns
(see `mppm`

).

It invokes `subfits`

to compute the fitted model for
each individual point pattern dataset, then calls
`plot.ppm`

to plot these individual models. These
individual plots are displayed using `plot.anylist`

,
which generates either a series of separate plot frames or an
array of plot panels on a single page.

##### Value

`NULL`

.

##### References

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

##### See Also

##### Examples

```
# NOT RUN {
# Synthetic data from known model
n <- 9
H <- hyperframe(V=1:n,
U=runif(n, min=-1, max=1))
H$Z <- setcov(square(1))
H$U <- with(H, as.im(U, as.rectangle(Z)))
H$Y <- with(H, rpoispp(eval.im(exp(2+3*Z))))
fit <- mppm(Y ~Z + U + V, data=H)
plot(fit)
# }
```

*Documentation reproduced from package spatstat, version 1.61-0, License: GPL (>= 2)*