In order to highlight the differences between our and the previously published approach one has to look at the confidence regions in the two dimensional parameter space. Table lists the one-dimensional marginal errors 1σ errors of the posterior distribution. This is in general a misleading statement and what it actually corresponds to is that the probability of finding the true value of the parameter in question around the MLE is 68.3%. For a one-dimensional Gaussian, this is exactly the 1-σ around the mean (which equals the MLE). If the underlying distribution is, however, non-Gaussian this interval changes, as does the two-dimensional contour. The results presented in table 4 therefore correspond to presenting results in the following way: