Description Usage Arguments Value Author(s) See Also Examples
A spatial vine copula is conditioned under the observations of all but one neighbour generating a conditional univariate distribution used for prediction.
1 | condSpVine(condVar, dists, spVine, n = 1000)
|
condVar |
the conditional variables |
dists |
the distances between the neighbours to adjust the spatial vine copula parameters. |
spVine |
the spatial vine copula |
n |
a proxy to the number of intervals to be used in the numerical integration. The intervals will not be split uniform with a shorter intervals at the corners of the copula. |
A function describing the conditional density.
Benedikt Graeler
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | data("spCopDemo")
calcKTauPol <- fitCorFun(bins, degree=3)
spCop <- spCopula(components=list(normalCopula(0.2), tCopula(0.2, dispstr = "un"),
frankCopula(1.2), normalCopula(0.2), claytonCopula(0.2),
claytonCopula(0.2), claytonCopula(0.2), claytonCopula(0.2),
claytonCopula(0.2), indepCopula()),
distances=c(0, bins$meanDists[1:9]),
spDepFun=calcKTauPol, unit="m")
spVineCop <- spVineCopula(spCop, vineCopula(4L))
dists <- list(c(473, 124, 116, 649))
condVar <- c(0.29, 0.55, 0.05, 0.41)
condDensity <- condSpVine(condVar,dists,spVineCop)
curve(condDensity)
mtext(paste("Dists:",paste(round(dists[[1]],0),collapse=", ")),line=0)
mtext(paste("Cond.:",paste(round(condVar,2),collapse=", ")),line=1)
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