I'm a new user of R and a novice user in copula R package.
I want to fit 3-dimensional t copula for my trivariate data. So I used the
command
t.cop <-
tCopula(c(0.785,0.283,0.613),dim=3,dispstr="un",df=6,df.fixed TRUE)
where c(0.785,0.283,0.613) is the correlation pattern of my data with 0.785
pearson correlation between variable 1-2, 0.283 correlation between 1-3 and
0.613 is the correlation between variable 2-3. In given command degree of
freedom (dof) is fixed at 6 and i'm checking p-value of the estimate using
gof copula using
gofCopula(t.cop,x,500) for 500 iterations, where x is my data vector. I'm
checking p-values of my each run by varying dofs from 2,3,...,6. But in
every run the value of cramer von-mises is changing but p-value is keeping
constant as 0.000998004, showing its a quite poor fit to data. Am i going
wrong any where? pls. suggest. As Most of the literature fitting t copula
shows dof in the range of generally 2-6 with significant p-values of the
estimate
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