dropROC {spatstat.model} | R Documentation |
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 |
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 |
... |
Arguments passed to |
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)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Ege Rubak rubak@math.aau.dk and Suman Rakshit Suman.Rakshit@curtin.edu.au.
References
Baddeley, A., Rubak, E., Rakshit, S. and Nair, G. (2025) ROC curves for spatial point patterns and presence-absence data. doi:10.48550/arXiv.2506.03414.
See Also
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)