composeSpCopula: Composing a bivariate Spatial Copula
In spcopula: Copula Driven Analysis - Multivariate, Spatial, Spatio-Temporal

Description Usage Arguments Value Author(s) Examples

A bivariate spatial copula is composed out of a set of bivariate copulas. These are combined using a convex linear combination with weights based on distances where for copulas with a 1-1 correspondence of Kendall's tau or Spearman's rho a dependence function providing measures of association based on distances might be used.

1	composeSpCopula(bestFit, families, bins, calcCor, range=max(bins$meanDists))

`bestFit`	A vector indicating the best fitting copula family index (as in `families`) per lag-class. If this vector is shorter than the actual number of bins, only these first bins will be used. It is an alternative way of setting a range.
`families`	The list of investigated families.
`bins`	The spatial bins used.
`calcCor`	Optional, some spatially dependent function providing values of Kendall's tau for distances.
`range`	The maximal distance to be used for the spatial copula. By default, the maximum distance provided by bins will be used.

A (spCopula) object.

Benedikt Graeler

1 2	composeSpCopula(c(1,1,2,3),families=list(frankCopula(.4), gumbelCopula(1.6),gumbelCopula(1.4)), bins=data.frame(meanDists=c(500,1000,1500,2000,2500)),range=2250)