Code covered by the BSD License
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LogLik(x,Nu,Sigma)
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MleRecursionForT(x,Nu,K,Toler...
this function computes recursively the ML estimators of the correlation
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[Nu,C]=StrucTMLE(X,K,Toleranc...
this function computes recursively the ML estimators of the correlation
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[W,F,U]=SeparateMargCop(X)
this function separates the empirical copula from the marginal distribution
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S_ReadMe.m
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View all files
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Estimation of Structured t-Copulas
by Attilio Meucci
Recursive routine to estimate structured correlation matrix and degrees of freedom
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function [Nu,C]=StrucTMLE(X,K,Tolerance)
% this function computes recursively the ML estimators of the correlation
% matrix and the d.o.g. of a t copula with isotropic structure
% see A. Meucci (2008) "Estimation of Structured T-Copulas"
% available at www.symmys.com > Research > Working Papers
Nus=[2 4 7 11 20 50]; % significant grid of potential degrees of freedom
LL=[]; % log-likelihood
[W,F,U]=SeparateMargCop(X); % extract copula
for s=1:length(Nus)
Nu=Nus(s);
Y=tinv(U,Nu);
C = MleRecursionForT(Y,Nu,K,Tolerance);
LL=[LL LogLik(Y,Nu,C)];
end
[a,Index]=max(LL);
Nu=Nus(Index);
C = MleRecursionForT(Y,Nu,K,Tolerance);
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