Fitting models to correlated data II (small samples, large correlations, and wrong models)

The estimation of experimental error, data correlation and model error by the analysis of the fit residuals in an ordered sequence of data [J. Mol. Spectrosc. 224 (2004) 73] is improved by a better insight in the calculation of the statistical relevant quantities. The biases previously observed for too small samples of data, very wrong models or highly correlated data, are partially corrected and this leads to better estimates in some extreme cases provided these unfavourable conditions are not combined. However, such results are always obtained with a decrease in accuracy.