bw.CvL: Cronie and van Lieshout's Criterion for Bandwidth Selection...

View source: R/bw.CvL.R

bw.CvLR Documentation

Cronie and van Lieshout's Criterion for Bandwidth Selection for Kernel Density


Uses Cronie and van Lieshout's criterion based on Cambell's formula to select a smoothing bandwidth for the kernel estimation of point process intensity.


   bw.CvL(X, ..., srange = NULL, ns = 16, sigma = NULL, warn=TRUE)



A point pattern (object of class "ppp").




Optional numeric vector of length 2 giving the range of values of bandwidth to be searched.


Optional integer giving the number of values of bandwidth to search.


Optional. Vector of values of the bandwidth to be searched. Overrides the values of ns and srange.


Logical. If TRUE, a warning is issued if the optimal value of the cross-validation criterion occurs at one of the ends of the search interval.


This function selects an appropriate bandwidth sigma for the kernel estimator of point process intensity computed by density.ppp.

The bandwidth \sigma is chosen to minimise the discrepancy between the area of the observation window and the sum of reciprocal estimated intensity values at the points of the point process

\mbox{CvL}(\sigma) = (|W| - \sum_i 1/\hat\lambda(x_i))^2

where the sum is taken over all the data points x_i, and where \hat\lambda(x_i) is the kernel-smoothing estimate of the intensity at x_i with smoothing bandwidth \sigma.

The value of \mbox{CvL}(\sigma) is computed directly, using density.ppp, for ns different values of \sigma between srange[1] and srange[2].


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 \colette. Adapted for spatstat by \spatstatAuthors.


Cronie, O and Van Lieshout, M N M (2018) A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions, Biometrika, 105, 455-462.

See Also

density.ppp, bw.optim.object.

Alternative methods: bw.diggle, bw.scott, bw.ppl, bw.frac.

For adaptive smoothing bandwidths, use bw.CvL.adaptive.


  if(interactive()) {
    b <- bw.CvL(redwood)
    plot(b, main="Cronie and van Lieshout bandwidth criterion for redwoods")
    plot(density(redwood, b))
    plot(density(redwood, bw.CvL))

spatstat.explore documentation built on May 29, 2024, 4:04 a.m.