Estimates the Kinhom function
A weighted, marked, planar point pattern (
A vector of distances. If
One of the point types. Default is all point types.
An estimation of the point pattern density, obtained by the
Kinhom is a cumulative, topographic measure of an inhomogenous point pattern structure.
By default, density estimation is performed at points by
density.ppp using the optimal bandwith (
bw.diggle). It can be calculated separately (see example), including at pixels if the point pattern is too large for the default estimation to succeed, and provided as the argument
Arbia et al. (2012) for example use another point pattern as a reference to estimate density.
Bivariate Kinhom is not currently supported.
An object of class
fv.object, which can be plotted directly using
The computation of
Kinhomhat relies on spatstat functions
Eric Marcon <[email protected]>
Baddeley, A. J., J. Moller, et al. (2000). Non- and semi-parametric estimation of interaction in inhomogeneous point patterns. Statistica Neerlandica 54(3): 329-350.
Arbia, G., G. Espa, et al. (2012). Clusters of firms in an inhomogeneous space: The high-tech industries in Milan. Economic Modelling 29(1): 3-11.
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data(paracou16) # Density of all trees lambda <- density.ppp(paracou16, bw.diggle(paracou16)) plot(lambda) # Reduce the point pattern to one type of trees V.americana <- paracou16[paracou16$marks$PointType=="V. Americana"] plot(V.americana, add=TRUE) # Calculate Kinhom according to the density of all trees r <- 0:30 plot(Kinhomhat(paracou16, r, "V. Americana", lambda), ./(pi*r^2) ~ r)
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