For autoregressive methods in general, Equation (1.13) can be solved uniquely for a chosen rank because c B and r B are required to have a very limiting and specific (Vandermonde) form, or a least-squares approximation of that form. Recent work describes successful use of the matrix pencil method for analyzing two-dimensional relaxometry data sets. In this report, output parameters are refined using least-squares optimization, as was done for the one-dimensional case. Complications arise for certain two-dimensional protocols including the longitudinal-transverse (T1-T2) measurement, where relaxation towards non-zero magnetization occurs in one or both dimensions. In these cases, rows (or columns) of the spectral matrix are overtly linearly dependent. Equation (1.13) must be appropriately modified in these cases.