# bw.voronoi

##### Cross Validated Bandwidth Selection for Voronoi Estimator of Intensity on a Network

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.

##### 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

##### 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)
# }
```

*Documentation reproduced from package spatstat, version 1.63-0, License: GPL (>= 2)*