spatstat (version 1.56-1)

objsurf: Objective Function Surface

Description

For a model that was fitted by optimisation, compute the values of the objective function in a neighbourhood of the optimal value.

Usage

objsurf(x, …)

# S3 method for dppm objsurf(x, ..., ngrid = 32, ratio = 1.5, verbose = TRUE)

# S3 method for kppm objsurf(x, ..., ngrid = 32, ratio = 1.5, verbose = TRUE)

# S3 method for minconfit objsurf(x, ..., ngrid = 32, ratio = 1.5, verbose = TRUE)

Arguments

x

Some kind of model that was fitted by finding the optimal value of an objective function. An object of class "dppm", "kppm" or "minconfit".

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 ngrid=32 would mean a 32 * 32 grid.

ratio

Number greater than 1 determining the range of parameter values to be considered. If the optimal parameter value is opt then the objective function will be evaluated for values between opt/ratio and opt * ratio.

verbose

Logical value indicating whether to print progress reports.

Value

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.

Details

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.

See Also

methods.objsurf, kppm, mincontrast

Examples

Run this code
# NOT RUN {
   fit <- kppm(redwood ~ 1, "Thomas")
   os <- objsurf(fit)

   if(interactive()) {
     plot(os)
     contour(os, add=TRUE)
     persp(os)
   }
# }

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