dkdevinecop {kdevine} | R Documentation |
Working with a kdevinecop
object
Description
A vine copula density estimate (stored in a kdevinecop
object)
can be evaluated on arbitrary points with dkevinecop
. Furthermore,
you can simulate from the estimated density with rkdevinecop
.
Usage
dkdevinecop(u, obj, stable = FALSE)
rkdevinecop(n, obj, U = NULL, quasi = FALSE)
Arguments
u |
|
obj |
|
stable |
logical; option for stabilizing the estimator: the estimated
pair copula density is cut off at |
n |
integer; number of observations. |
U |
(optional) |
quasi |
logical; the default ( |
Value
A numeric vector of the density/cdf or a n x 2
matrix of
simulated data.
Author(s)
Thomas Nagler
References
Nagler, T., Czado, C. (2016)
Evading the curse of dimensionality in nonparametric density estimation.
Journal of Multivariate Analysis 151, 69-89 (doi:10.1016/j.jmva.2016.07.003)
Dissmann, J., Brechmann, E. C., Czado, C., and Kurowicka, D. (2013).
Selecting and estimating regular vine copulae and application to financial returns.
Computational Statistics & Data Analysis, 59(0):52–69.
See Also
kdevinecop
,
dkdecop
,
rkdecop
,
ghalton
Examples
data(wdbc, package = "kdecopula") # load data
u <- VineCopula::pobs(wdbc[, 5:7], ties = "average") # rank-transform
fit <- kdevinecop(u) # estimate density
dkdevinecop(c(0.1, 0.1, 0.1), fit) # evaluate density estimate