View source: R/densitylppVoronoi.R
bw.voronoi | R Documentation |
Uses cross-validation to select a smoothing bandwidth for the Voronoi estimate of point process intensity on a linear network.
bw.voronoi(X, ..., probrange = c(0.2, 0.8), nprob = 10,
prob = NULL, nrep = 100, verbose = TRUE, warn=TRUE)
X |
Point pattern on a linear network (object of class |
... |
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 |
nrep |
Number of simulated realisations to be used for the computation. |
verbose |
Logical value indicating whether to print progress reports. |
warn |
Logical. If |
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
.
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
.
and \mehdi.
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.
densityVoronoi.lpp
, bw.optim.object
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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