Figure 5

Joint distribution in the threonine model. Left: eigenvalues of the covariance matrices C₍₀₎ (light blue - - for prior), C₍₁₎ (dark blue -.-, first posterior), C₍₂₎ (purple —, second posterior). The width of the parameter distribution decreases in both estimation steps. Some eigenvalues become very small in the second posterior; they represent well-defined parameter combinations. Centre: eigenvectors for the first posterior. Each row of the matrix corresponds to an eigenvector (normalised to a maximal value of 1 for the elements). The corresponding eigenvalues are shown in the box on the left. The distribution of energy constants is well-defined in some directions (eigenvectors on top, with low eigenvalues) and uncertain in other directions (bottom, high eigenvalues). The k^M and k^I values are uncorrelated (described by individual eigenvectors). Right: the eigenvectors of the second posterior fall into three groups: (i) eigenvectors for well-defined directions, coupling all sorts of parameters (top), (ii) less well-defined combinations of k^M and k^I values (centre), and (iii) poorly defined combinations of energy constants (bottom).