objsurf | R Documentation |
For a model that was fitted by optimisation, compute the values of the objective function in a neighbourhood of the optimal value.
objsurf(x, ...) ## S3 method for class 'dppm' objsurf(x, ..., ngrid = 32, xlim=NULL, ylim=NULL, ratio = 1.5, verbose = TRUE) ## S3 method for class 'kppm' objsurf(x, ..., ngrid = 32, xlim=NULL, ylim=NULL, ratio = 1.5, verbose = TRUE) ## S3 method for class 'minconfit' objsurf(x, ..., ngrid = 32, xlim=NULL, ylim=NULL, ratio = 1.5, verbose = TRUE)
x |
Some kind of model that was fitted
by finding the optimal value of an objective function.
An object of class |
... |
Extra arguments are usually ignored. |
ngrid |
Number of grid points to evaluate along each axis.
Either a single integer, or a pair of integers.
For example |
xlim,ylim |
Optional. Numeric vectors of length 2, specifying the limits for the two parameters to be considered. |
ratio |
Number greater than 1 determining the range of parameter values
to be considered. If the optimal parameter value is |
verbose |
Logical value indicating whether to print progress reports. |
The object 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:
an object of class "dppm"
representing a
determinantal point process.
See dppm
.
an object of class "kppm"
representing a
cluster point process or Cox point process.
See kppm
.
an object of class "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
.
An object of class "objsurf"
which can be
printed and plotted.
Essentially a list containing entries x
, y
, z
giving the parameter values and objective function values.
There are methods for plot
, print
, summary
,
image
, contour
and persp
.
and \ege.
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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