Abstract
Suppose estimates are available for correlations between pairs of variables, but that the matrix of correlation estimates is negative definite. We present two methods for adjusting the initial estimates to form a proper correlation matrix. The first is based on the maximum likelihood principle and the second is a Bayesian approach. We discuss and illustrate the use of different likelihoods and priors.