  We propose a Cholesky factor parameterization of correlation matrices that
facilitates a priori restrictions on the correlation matrix. It is a smooth and
differentiable transform that allows additional boundary constraints on the
correlation values. Our particular motivation is random sampling under
positivity constraints on the space of correlation matrices using MCMC methods.
