copula (version 0.9-5)

fitMvdc: Estimation of multivariate models defined via copulas

Description

Fits a copula-based multivariate distribution to multivariate data.

Usage

loglikMvdc(param, x, mvdc, suppressMessages=FALSE)
fitMvdc(data, mvdc, start, optim.control = list(NULL), method = "BFGS")

Arguments

param

a vector of parameter values. When specifying parameters for mvdc objects the parameters should be ordered with the marginals first and the copula parameters last. When the mvdc object has marginsIdentical = TRUE

x

a data matrix.

mvdc

a "mvdc" object.

suppressMessages

logical, if TRUE, warnings messages from evaluating loglikelihood at invalid parameter values are suppressed.

data

a data matrix.

start

a vector of starting value for "param". See "param" above for ordering of this vector.

optim.control

a list of controls to be passed to "optim".

method

the method for optim.

Value

• The return value "loglikMvdc" is the loglikelihood evaluated for the given value of "param".

  The return value of "fitMvdc" is an object of class "fitMvdc" containing slots:

• estimate
  the estimate of the parameters.
• var.est
  large-sample variance estimate of the parameter estimator.
• loglik
  loglikelihood at "est".
• copula
  the fitted copula.

See Also

Copula, fitCopula, gofCopula.

Examples

gumbel.cop <- gumbelCopula(3, dim=2)
myMvd <- mvdc(gumbel.cop, c("exp","exp"), list(list(rate=2),list(rate=4)))
x <- rmvdc(myMvd, 1000)
fit <- fitMvdc(x, myMvd, c(1,1,2))
fit

#### Roger Koenker prepared a demo illustrating MLE for a Clayton AR(1)
#### copula model with identical, user-defined Student marginals
## demo("QARClayton")