You are doing inv(xTrain.'*xTrain) but rank(xTrain) is only 1
This is related to your passing in the undocumented fourth parameter to mvnrnd, which you give as 10. The third and fourth parameter together do not give an output size: the output size is determined by the third parameter (a size) and the length of the diagonal of the second parameter.
The undocumented fourth parameter is:
% R = MVNRND(MU,SIGMA,N,T) supplies the Cholesky factor T of
% SIGMA, so that SIGMA(:,:,J) == T(:,:,J)'*T(:,:,J) if SIGMA is a 3D array or SIGMA
% == T'*T if SIGMA is a matrix. No error checking is done on T.
You encounter the line
r = randn(n,size(T,1),'like',outtype) * T + mu;
where n is 1000 (your third parameter) and T is 10 so size(T,1) is 1 and mu is the vector of zeros you passed in as your first parameter, replicated to have n rows, so 1000 x 10 of zeros. This is then a 1000 x 1 vector plus a 1000 x 10 array of zeros.
If you were running R2016a or earlier you would have received an error, but in R2016b or later the operation is equivalent to
bsxfun(@plus, randn(n,size(T,1),'like',outtype) * T, mu)
so the 1000 x 1 vector is replicated to 1000 x 10 and the 1000 x 10 array of zeros is added. This gives you a 1000 x 10 matrix in which all of the rows are identical, and the rank of that is going to be 1. Multiply it by its transpose and the rank of the result cannot be greater than 1 so you cannot inv() it.
