spatstat (version 1.61-0)

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, verbose = TRUE)

Arguments

X

Point pattern on a linear network (object of class "lpp").

…

Ignored.

probrange

Numeric vector of length 2 giving the range of bandwidths (retention probabilities) to be assessed.

nprob

Integer. Number of bandwidths to be assessed.

prob

Optional. A numeric vector of bandwidths (retention probabilities) to be assessed. Entries must be probabilities between 0 and 1. Overrides nprob and probrange.

nrep

Number of simulated realisations to be used for the computation.

verbose

Logical value indicating whether to print progress reports.

Value

A numerical value giving the selected bandwidth. The result also belongs to the class "bw.optim" which can be plotted.

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, in press.

See Also

densityVoronoi.lpp

Examples

# NOT RUN {
   np <- if(interactive()) 10 else 3
   nr <- if(interactive()) 100 else 2
   b <- bw.voronoi(spiders, nprob=np, nrep=nr)
   b
   plot(b)
# }

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