fitMvdc {copula}R Documentation

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, only the parameters of one marginal should be specified.
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.

Note

User-defined marginal distribution can be used as long as the "{dpq}" functions are defined. See demo(QARClayton) prepared by Roger Koenker <rkoenker@uiuc.edu>.

When covariates are available for marginal distributions or for the copula, one can construct the loglikelihood function and feed it to "optim" to estimate all the parameters.

Finally, note that the fitting functions generate error messages because invalid parameter values are tried during the optimization process (see optim).

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, uder-defined Student marginals
## demo("QARClayton")

[Package copula version 0.8-3 Index]