copula (version 0.5-8)

fitCopula: Maximum Likelihood Estimation of Copula Models

Description

Fit a copula model to multivariate data.

Usage

loglikCopula(param, x, copula)
loglikMvdc(param, x, mvdc)
fitCopula(data, copula, start, lower=NULL, upper=NULL,
          optim.control = list(NULL), method = "BFGS")
fitMvdc(data, mvdc, start, optim.control = list(NULL), method = "BFGS")

Arguments

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

lower, upper

bounds on the variables for the '"L-BFGS-B"' method.

optim.control

a list of control to be passed to optim

method

the method for optim

Value

• 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

References

Yan (2006), Multivariate Modeling with Copulas and Engineering Applications. In Handbook of Engineering Statistics, Ed. Pham, Springer.

See Also

Copula, mvdc

Examples

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))
fit