fitCopula {copula} | R Documentation |
Fit a copula model to multivariate data.
loglikCopula(param, x, copula) loglikMvdc(param, x, mvdc) fitCopula(data, copula, start, optim.control = list(NULL), method = "BFGS") fitMvdc(data, mvdc, start, optim.control = list(NULL), method = "BFGS")
param |
a vector of parameter values |
x |
a data matrix |
copula |
a 'copula' object |
mvdc |
a 'mvdc' object |
data |
a data matrix |
start |
a vector of starting value for param |
optim.control |
a list of control to be passed to optim |
method |
the method for optim |
The return values of 'loglikCopula' and 'loglikMvdc' are the
loglikelihood evaluated at the given value of 'param'.
The return values of 'fitCopula' and 'fitMvdc' are an object of
class 'fitCopula' and 'fitMvdc', respectively, containing slots:
est |
the estimate of the parameters |
var.est |
variance matrix of the estimate |
loglik |
loglikelihood at est |
fit |
the result of optim |
When covariates are available for marginal distributions or copula, one can construct loglikelihood function and feed it to optim to estimate all the parameters.
Jun Yan <jyan@stat.uiowa.edu>
Yan (2006) Multivariate Modeling with Copulas and Engineering Applications. In Handbook of Engineering Statistics, Ed. Pham, Springer.
gmb <- gumbelCopula(3, dim=2) myMvd <- mvdc(gmb, c("exp","exp"), list(list(rate=2),list(rate=4))) x <- rmvdc(myMvd, 1000) fit <- fitMvdc(x, myMvd, c(1,1,2))