Hello
> Berwin A Turlach writes:
> That you don't have the package Rmpfr installed? And it seems to be
> needed for the higher dimension. On my machine it works:
>
Thanks for the lead,
Best regards,
Jeremie
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R-help@r-project.org mailing list -
Hello,
In a situation where the dimension is high and the parameter is close to
the bound computing the density of the gumbel copula throws the following
error.
library(copula)
dCopula(rep(0.5,127),gumbelCopula(1.19,127),log=TRUE)
Loading required namespace: Rmpfr
Failed with error: ‘there is n
Dear all,
In an attempt to generate a sample of observations from a four dimensional
copula from the package Copula, I got the following warning message and all the
observations are NA's:
Warning messages:
1: In rmvnorm(n, sigma = getSigma(copula)) :
sigma is numerically not positive definite
2
> Lucas Holland
> on Sun, 17 Mar 2013 16:26:41 +0100 writes:
> Hey all,
> I'm trying to construct a 7-dimensional normal copula using the copula
package. I'd like to supply as parameter a randomly generated correlation
matrix (that I'll convert to a vector so I can feed it t
Hey all,
I'm trying to construct a 7-dimensional normal copula using the copula package.
I'd like to supply as parameter a randomly generated correlation matrix (that
I'll convert to a vector so I can feed it to the normalCopula function). What
order do the pairwise correlations inside that vec
: Mittwoch, 22. April 2009 09:45
>An: r-help@r-project.org
>Betreff: [R] Copula package
>
>
>Hi R-users,
>
>I would like to use the copula package. I the package plus
>the mvtnorm and try to run the example given, but I got the
>following message:
>
>install.p
Hi R-users,
I would like to use the copula package. I the package plus the mvtnorm and
try to run the example given, but I got the following message:
install.packages(repos=NULL,pkgs="c:\\Tinn-R\\copula_0.8-3.zip")
norm.cop <- normalCopula(c(0.5, 0.6, 0.7), dim = 3, dispstr = "un")
t.cop <- t
Dears,
I calculated correlation matrix using 144 variables with a given function:
cor_flows_vec=cor()
Then I defined a normal copula with the above correlation matrix
myCop=normalCopula(param=cor_flows_vec, dim = 144, dispstr = "un")
Then I created a multivariate distribution with our defined c
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