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I've come across several possible solutions which I'd like to state:įor a positive definite matrix the determinant is positive. However, there seem to be some confusion about the result if the matrix is only positive semi-definite, so be carefull if this is the case. In the documentation for chol it is also preferred over eigs to check for positive definiteness. In my case determines the transition from positive definite to not positive definite (meaning first singular then indefinite), and is also computationally very efficient. Matlabs command chol have the possibility to return a value p which is zero if the matrix is positive definite. I seem to have solved my particular problem. by another way determine when A becomes singular (when changing a variable in A).without doubt find the smallest eigenvalue with 'eigs', or.However, the eigenvalues seem to behave oddly, and I am not sure if I actually find the true lowest one. Where i look in the range of the last lowest eigenvalue. Then I've tried defining a shift value like for i = 1:10

Matlab cannot get the lowest eigenvalue to converge. I've tried D = eigs(A,1,'smallestabs')īy which I lose the sign of the eigenvalue, and by D = eigs(A,1,'smallestreal') I don't trust the determinants so I am looking at the eigenvalues, but I don't have the memory (or time) to calculate all n eigenvalues, and I am only interested in the smallest - and in particular when it changes sign from positive to negative. I am to determine when A becomes singular. A goes from being positive definite to singular to indefinite for a particular variable which is changed. Even though A is positive definite it is close to singular. In Matlab I have a real and symmetric n x n matrix A, where n > 6000.