In the extant literature a suggestion has been made to solve the nearest correlation matrix problem by a modified von Neumann approximation. In this paper it has been shown that obtaining the nearest positive semi-definite matrix of a given negative definite correlation matrix by such method is either infeasible or suboptimal. First, if a given matrix is already positive semi-definite, there is no need to obtain any other semi-definite matrix closest to it. When the given matrix is negative definite (Q), then only we seek a positive semi-definite matrix closest to it. Then the proposed procedure fails as we cannot find log(Q). Then, if we replace negative eigenvalues of Q by a zero or near-zero values, we obtain a positive-definite matrix, but it is not nearest to the Q matrix; there are indeed other procedures to obtain better approximation
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