objsurf(x, ...)
"objsurf"(x, ..., ngrid = 32, ratio = 1.5, verbose = TRUE)
"objsurf"(x, ..., ngrid = 32, ratio = 1.5, verbose = TRUE)
"objsurf"(x, ..., ngrid = 32, ratio = 1.5, verbose = TRUE)
"dppm"
, "kppm"
or "minconfit"
.
ngrid=32
would mean a 32 * 32
grid.
opt
then the objective function will be evaluated for
values between opt/ratio
and opt * ratio
.
"objsurf"
which can be
printed and plotted.
Essentially a list containing entries x
, y
, z
giving the parameter values and objective function values.
x
should be some kind of model that was fitted
by maximising or minimising the value of an objective function.
The objective function will be evaluated on a grid of
values of the model parameters. Currently the following types of objects are accepted:
"dppm"
representing a
determinantal point process.
See dppm
.
"kppm"
representing a
cluster point process or Cox point process.
See kppm
.
"minconfit"
representing a
minimum-contrast fit between a summary function and its
theoretical counterpart.
See mincontrast
.
The result is an object of class "objsurf"
which can be
printed and plotted: see methods.objsurf
.
methods.objsurf
,
kppm
,
mincontrast
fit <- kppm(redwood ~ 1, "Thomas")
os <- objsurf(fit)
if(interactive()) {
plot(os)
contour(os, add=TRUE)
persp(os)
}
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