In some cases, a correlation matrix may be singular
because of the multicollinearity in data, and it may
become non-Gramian because of computational inaccuracies.
In such cases, popular methods of factor extraction,
such as maximum likelihood factor analysis,
image factor analysis, and canonical factor analysis,
cannot be used because of computational difficulties.
This article provides a simple heuristic procedure for
converting such a matrix into a proper matrix, so that
maximum likelihood factor analysis may be performed.