plot.mppm | R Documentation |
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.
## S3 method for class 'mppm'
plot(x, ...,
trend=TRUE, cif=FALSE, se=FALSE,
how=c("image", "contour", "persp"),
main)
x |
A point process model fitted to multiple point patterns,
typically obtained from
the model-fitting algorithm |
... |
Arguments passed to |
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. |
main |
Character string for the main title of the plot. |
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.
NULL
.
, Ida-Maria Sintorn and Leanne Bischoff. Implemented by \adrian
\rolfand \ege
plot.ppm
,
mppm
,
plot.listof
# 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)
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