View source: R/BiCopHfuncDeriv.R
| BiCopHfuncDeriv | R Documentation |
This function evaluates the derivative of a given conditional parametric bivariate copula (h-function) with respect to its parameter(s) or one of its arguments.
BiCopHfuncDeriv(
u1,
u2,
family,
par,
par2 = 0,
deriv = "par",
obj = NULL,
check.pars = TRUE
)
u1, u2 |
numeric vectors of equal length with values in |
family |
integer; single number or vector of size |
par |
numeric; single number or vector of size |
par2 |
integer; single number or vector of size |
deriv |
Derivative argument |
obj |
|
check.pars |
logical; default is |
If the family and parameter specification is stored in a BiCop()
object obj, the alternative version
BiCopHfuncDeriv(u1, u2, obj, deriv = "par")
can be used.
A numeric vector of the conditional bivariate copula derivative
of the copula family,
with parameter(s) par, par2,
with respect to deriv,
evaluated at u1 and u2.
Ulf Schepsmeier
Schepsmeier, U. and J. Stoeber (2014). Derivatives and Fisher
information of bivariate copulas. Statistical Papers, 55 (2), 525-542.
https://link.springer.com/article/10.1007/s00362-013-0498-x.
RVineGrad(), RVineHessian(),
BiCopDeriv2(), BiCopDeriv2(),
BiCopHfuncDeriv(), BiCop()
## simulate from a bivariate Student-t copula
set.seed(123)
cop <- BiCop(family = 2, par = -0.7, par2 = 4)
simdata <- BiCopSim(100, cop)
## derivative of the conditional Student-t copula
## with respect to the first parameter
u1 <- simdata[,1]
u2 <- simdata[,2]
BiCopHfuncDeriv(u1, u2, cop, deriv = "par")
## estimate a Student-t copula for the simulated data
cop <- BiCopEst(u1, u2, family = 2)
## and evaluate the derivative of the conditional copula
## w.r.t. the second argument u2
BiCopHfuncDeriv(u1, u2, cop, deriv = "u2")
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