Dimensions of matrices being concatenated are not consistent.

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Hi, im having trouble in running a programm for the following reason: Dimensions of matrices being concatenated are not consistent.

vector names correspond to the forecast error decomposition of variance, as mentioned in %P=chol(Omega); Choleski factorization

However vectors have the same number of columns:

Y=data;
% will print results to the MATLAB command window
% set flag for Sim's correction factor
sims = 1;
maxlag = 12;
minlag = 1;
lrratio(Y,maxlag,minlag,sims);
%
T=length(Y);  
NAR=1;  
M=50;   
H=12;   
%
N=size(Y,2);
results=fvar(Y,NAR);
MPHI=mphi(results,NAR,N);
%matrix of variances y covariances
for i = 1:N
    err(:,i) = results(i).resid;
end
Omega = err'*err/rows(err);
%P=chol(Omega); Choleski factorization 
P=eye(N);
vnames =  ['UNICREDIT ',
           'CREDIT SUISSE      ',    
           'SANTANDER   ',
           'UBS ',
           'ING  ',
           'DEUTSCHE BANK    ',
           'HSBC ',
           'SOCIETE GENERALE   ',
           'CREDIT AGRICOLE     ',
           'BNP PARIBAS       ',     
           'BARCLAYS '];
vnames1 =  ['unicredit ',
            'credit suisse ',    
            'santander  ',
            'ubs ',
            'ing  ',
            'deutsche bank ',
            'hsbc ',
            'societe generale ',
            'credit agricole ',
            'bnp paribas  ',
            'barclays  '];
names={'UNICREDIT ' 'CREDIT SUISSE ' 'SANTANDER ' 'UBS ' 'ING ' 'DEUTSCHE BANK ' 'HSBC ' 'SOCIETE GENERALE ' 'CREDIT AGRICOLE ' 'BNP ' 'BARCLAYS '};