spatstat.linnet: bw.voronoi – R documentation

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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, warn=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.
`warn`	Logical. If `TRUE`, issue a warning if the maximum of the cross-validation criterion occurs at one of the ends of the search interval.

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.

Value

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

Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk and Mehdi Moradi.

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.

Examples

np <- if(interactive()) 10 else 3
   nr <- if(interactive()) 100 else 2
   b <- bw.voronoi(spiders, nprob=np, nrep=nr)
   b
   plot(b)

spatstat.linnet

Linear Networks Functionality of the 'spatstat' Family

v2.1-1

GPL (>= 2)

Authors

Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Ottmar Cronie [ctb], Tilman Davies [ctb], Greg McSwiggan [ctb], Suman Rakshit [ctb]

Initial release

2021-03-28