dropROC: ROC Curves for all Single Term Deletions from a Model

In spatstat.model: Parametric Statistical Modelling and Inference for the 'spatstat' Family

ROC Curves for all Single Term Deletions from a Model

Description

Given a fitted point process model, consider dropping each possible term in the model, and compute the ROC curve for the dropped covariate.

Usage

dropROC(object, scope = NULL, high=TRUE, ...)

Arguments

object	A fitted point process model (object of class "ppm", "kppm", "dppm", "slrm" or "lppm").
scope	A formula or a character vector specifying the terms to be considered for deletion. The default is all possible terms.
high	Argument passed to roc to specify whether the ROC curves should be based on high or low values of the covariates. Either a logical value, or a logical vector of the same length as scope.
...	Arguments passed to as.mask to control the pixel resolution used for calculation.

Details

This function is like drop1 in that it considers each possible term in the model object (or only the terms listed in the scope argument), deletes each such term from the model, and measures the change in the model. In this case the change is measured by computing the ROC curve for the deleted covariate, using the updated model as a baseline.

Value

A named list containing the ROC curves for each possible deletion. The individual entries belong to class "fv", so they can be plotted. The list belongs to the class "anylist" so it can be plotted in its entirety.

Author(s)

\rocketAuthors

.

References

\rocpaper

See Also

dropply, addROC, roc.ppm.

Examples

  dimyx <- if(interactive()) NULL else 32
  fut <- ppm(bei ~ grad + elev, data=bei.extra)
  z <- dropROC(fut, dimyx=dimyx)
  plot(z)

  ## how to compute AUC for each 
  sapply(z, auc)

spatstat.model documentation built on Nov. 5, 2025, 5:39 p.m.