dcopula.gauss {QRMlib} | R Documentation |
evaluates density of Gauss copula
dcopula.gauss(u, P, logvalue=FALSE)
u |
matrix of dimension n times d, where d is the dimension of the copula and n is the number of vector values at which to evaluate density |
P |
correlation matrix of Gauss copula |
logvalue |
whether or not log density values should be returned (useful for ML) |
see pages 197 and 234 in QRM
vector of density values of length n
dmnorm
,
dcopula.clayton
,
dcopula.t
,
dcopula.gumbel
ll <- c(0.01,0.99); #create perspective plot for bivariate density: BiDensPlot(func=dcopula.gauss,xpts=ll,ypts=ll,P=equicorr(2,0.5));