1. The returned object is of class 'cGARCHfit'. Try getting help by typing ?'cGARCHfit-class'. This will bring up all the methods available to use on the object e.g. show(cfit), coef(cfit) and rcor(cfit).
2.rcor(cfit) returns an array of the conditional correlation.
3-4 Try searching first on http://www.rseek.org/.

Finally, the 'rmgarch.tests' folder in the installation directory of the package contains many examples which you might find helpful.

-Alexios

On 08/05/2012 01:13, Alex Fei wrote:
Hi

I am trying to implement a typical GARCH-Copula with DCC for dynamic
correlations. Is there someone could give me an example codes how it can be
done? I have implemented  this in Matlab, but don't know how to get a start
in R. I have googled around and found rmgarch package can give it a go.

Below is what I did:
library(rmgarch)
data(dji30ret)
Data<- dji30ret[, 1:3, drop = FALSE]
uspec<- ugarchspec(mean.model = list(armaOrder = c(0,0), include.mean =
FALSE), variance.model = list(garchOrder = c(1,1), model = "sGARCH"),
distribution.model = "std")
cspec<- cgarchspec(uspec = multispec( replicate(3, uspec) ), VAR = FALSE,
robust = FALSE, lag = 1, lag.max = NULL,                  lag.criterion =
c("AIC", "HQ", "SC", "FPE"), external.regressors = NULL, robust.control =
list(gamma = 0.25, delta = 0.01, nc = 10, ns = 500), dccOrder = c(1, 1),
asymmetric = FALSE, distribution.model = list(copula =  "mvt", method =
"ML", time.varying = TRUE, transformation = "parametric"), start.pars =
list(), fixed.pars = list())
cfit<- cgarchfit(cspec, data =Data, spd.control = list(lower = 0.1, upper
= 0.9, type = "pwm", kernel = "epanech"),fit.control = list(eval.se =
TRUE, trace = TRUE, stationarity = TRUE),solver = "solnp", solver.control
= list(), out.sample = 0, parallel = FALSE, parallel.control = list(pkg =
c("multicore", "snowfall"), cores = 2), fit = NULL, VAR.fit = NULL)

my questions are:
1) (very silly) how to get the estimated parameters (incl. s.e. p-value)?
2) how to plot the dynamics of correlation?
3) how to perform goodness-of-fit tests for marginal estimations?
4) how to perform  goodness-of-fit tests for copula?

I will appreciate for any help! Thank you

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