A kernel density estimate of the copula density is visualized. The function
provides the same options as plot.BiCop(). Further arguments can
be passed to kdecopula::kdecop() to modify the estimate. The
kdecopula::kdecopula-package() must be installed to use
this function.
BiCopKDE(u1, u2, type = "contour", margins, size, kde.pars = list(), ...)Arguments
- u1, u2
numeric vectors of equal length with values in \([0,1]\).
- type
plot type; either
"contour"or"surface"(partial matching is activated) for a contour or perspective/surface plot respectively.- margins
only relevant for types
"contour"and"surface"; options are:"unif"for the original copula density,"norm"for the transformed density with standard normal margins,"exp"with standard exponential margins, and"flexp"with flipped exponential margins. Default is"norm"fortype = "contour", and"unif"fortype = "surface"."norm"for the transformed density with standard normal margins (partial matching is activated). Default is"norm"fortype = "contour", and"unif"fortype = "surface".- size
integer; the plot is based on values on a
size x sizegrid; default is 100 fortype = "contour", and 25 fortype = "surface".- kde.pars
list of arguments passed to
kdecopula::kdecop().- ...
optional arguments passed to
contour()orwireframe().
Details
For further details on estimation see kdecopula::kdecop().
Examples
# simulate data from Joe copula
cop <- BiCop(3, tau = 0.3)
u <- BiCopSim(1000, cop)
contour(cop) # true contours
# kernel contours with standard normal margins
BiCopKDE(u[, 1], u[, 2])
#> Error in BiCopKDE(u[, 1], u[, 2]): The 'kdecopula' package must be installed.
BiCopKDE(u[, 1], u[, 2], kde.pars = list(mult = 0.5)) # undersmooth
#> Error in BiCopKDE(u[, 1], u[, 2], kde.pars = list(mult = 0.5)): The 'kdecopula' package must be installed.
BiCopKDE(u[, 1], u[, 2], kde.pars = list(mult = 2)) # oversmooth
#> Error in BiCopKDE(u[, 1], u[, 2], kde.pars = list(mult = 2)): The 'kdecopula' package must be installed.
# kernel density with uniform margins
BiCopKDE(u[, 1], u[, 2], type = "surface", zlim = c(0, 4))
#> Error in BiCopKDE(u[, 1], u[, 2], type = "surface", zlim = c(0, 4)): The 'kdecopula' package must be installed.
plot(cop, zlim = c(0, 4)) # true density
# kernel contours are also used in pairs.copuladata
data(daxreturns)
data <- as.copuladata(daxreturns)
pairs(data[c(4, 5, 14, 15)])
#> Error in (function (u1, u2, type = "contour", margins, size, kde.pars = list(), ...) { if (!requireNamespace("kdecopula", quietly = TRUE)) stop("The 'kdecopula' package must be installed.") args <- preproc(c(as.list(environment()), call = match.call()), check_u, remove_nas, check_if_01, na.txt = " Only complete observations are used.") list2env(args, environment()) args <- list(udata = cbind(u1, u2)) if (all(colnames(args$udata) == c("u1", "u2"))) args$udata <- unname(args$udata) args <- modifyList(args, kde.pars) est <- do.call(kdecopula::kdecop, args) if (missing(margins)) { margins <- switch(type, contour = "norm", surface = "unif") } return(plot(est, type = type, margins = margins, size = size, ...))})(u1 = c(0.828793223605221, 0.563928601045794, 0.596105082080661, 0.422989677071629, 0.426280538373799, 0.250871521532833, 0.307508168954636, 0.209134117395052, 0.772187568232017, 0.370202231451089, 0.242346738780308, 0.229610858681299, 0.326207290206335, 0.275122089336635, 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