Rolling window with Copulas - r

Question

I would like to apply a rolling window to fit a student t Copula and then to do a forecast based on the results from the fitting process. I already tried it with a for loop, but it always state errors according to the fit Copula command.
#Students t Copula
windowsSize <- 4000 # training data size
testsize <- 351 # number of observations to forecast
for(k in 0:33) # run 34 experiments
{
A <- k*testsize + 1
B <- A + windowsSize - 1
start_obs <- A
end_obs <- B
lgYen_roll <- lgYenUSD[A:B]
lgEuro_roll <- lgEuroUSD[A:B]
ElgYen_roll <- ElgYenUSD[A:B]
ElgEuro_roll <- ElgEuroUSD[A:B
StdlgYen_roll <- StdlgYenUSD[A:B]
StdlgEuro_roll <- StdlgEuroUSD[A:B]
CopYenEuro_roll <- pobs(as.matrix(cbind(lgYen_roll,lgEuro_roll)))
YenEuro_fit_t_roll <- fitCopula(t.cop,CopYenEuro_roll,method=c('ml'), posDef = is(t.cop, "ellipCopula"),
start = NULL, lower = NULL, upper = NULL,
optim.method = optimMeth(t.cop, method,dim=d),
optim.control = list(maxit=1000),
estimate.variance = NA, hideWarnings = FALSE)
Here occurs already the first error: "Error in if (any(u < 0) || any(u > 1)) stop("'u' must be in [0,1] -- probably rather use pobs(.)") :
missing value where TRUE/FALSE needed"
CO_YenEuro_roll_rho <- coef(YenEuro_fit_t_roll)[1]
CO_YenEuro_roll_df <- coef(YenEuro_fit_t_roll)[2]
YenEurocopula_dist_t_roll <- mvdc(copula=tCopula(param = CO_YenEuro_roll_rho,dim=2), margins=c("norm","norm"),
paramMargins = list(list(mean=ElgYen_roll, sd=StdlgYen_roll),
list(mean=ElgEuro_roll, sd=StdlgEuro_roll)),
check = TRUE, fixupNames = TRUE)
YenEurocopula_random_t_roll.dist <- rMvdc(351,YenEurocopula_dist_t_roll)
#Prediction
A <- B + 1
B <- B + testsize
lgYen_roll <- lgYenUSD[A:B]
lgEuro_roll <- lgEuroUSD[A:B]
ElgYen_roll <- ElgYenUSD[A:B]
ElgEuro_roll <- ElgEuroUSD[A:B]
StdlgYen_roll <- StdlgYenUSD[A:B]
StdlgEuro_roll <- StdlgEuroUSD[A:B]
predict_EXT <- matrix(0, testsize, 1)
for(i in 1:testsize) # do the forecast based on the Copula Fit results
{
predict_EXT[i] <- fitCopula(t.cop,CopYenEuro_rolling[i],method=c('ml'), posDef = is(t.cop, "ellipCopula"),
start = NULL, lower = NULL, upper = NULL,
optim.method = optimMeth(t.cop, method,dim=d),
optim.control = list(maxit=1000),
estimate.variance = NA, hideWarnings = TRUE)
YenEurocopula_dist_t_roll <- mvdc(copula=tCopula(param = CO_YenEuro_roll_rho[i],dim=2), margins=c("norm","norm"),
paramMargins = list(list(mean=ElgYen_roll[i], sd=StdlgYen_roll[i]),
list(mean=ElgEuro_roll[i], sd=StdlgEuro_roll[i])),
check = TRUE, fixupNames = TRUE)
YenEurocopula_random_t_roll.dist <- rMvdc(351,YenEurocopula_dist_t_roll[i])
}}
Maybe someone has a solution to this problem?