spatstat.linnet (version 3.4-0)

bw.voronoi: Cross Validated Bandwidth Selection for Voronoi Estimator of Intensity on a Network

Description

Uses cross-validation to select a smoothing bandwidth for the Voronoi estimate of point process intensity on a linear network.

Usage

bw.voronoi(X, ..., probrange = c(0.2, 0.8), nprob = 10,
           prob = NULL, nrep = 100,
           metric=c("shortestpath", "Euclidean"),
           verbose = TRUE, warn=TRUE)

Value

A single numerical value giving the selected bandwidth. The result also belongs to the class "bw.optim"

(see bw.optim.object) which can be plotted to show the bandwidth selection criterion as a function of sigma.

Details

This function uses likelihood cross-validation to choose the optimal value of the thinning fraction f (the retention probability) to be used in the smoothed Voronoi estimator of point process intensity densityVoronoi.lpp.

References

Moradi, M., Cronie, 0., Rubak, E., Lachieze-Rey, R., Mateu, J. and Baddeley, A. (2019) Resample-smoothing of Voronoi intensity estimators. Statistics and Computing 29 (5) 995--1010.

See Also

densityVoronoi.lpp, bw.optim.object

Examples

   if(interactive()) {
     X <- spiders
     np <- 10
     nr <- 100
   } else {
     X <- runiflpp(4, simplenet)
     np <- 3
     nr <- 2
   }
   b <- bw.voronoi(X, nprob=np, nrep=nr)
   b
   plot(b)
   bE <- bw.voronoi(X, nprob=np, nrep=nr, metric="E")
   bE