Structural identification with systematic errors and unknown uncertainty dependencies
In model-based data-interpretation, uncertainty dependencies are in many cases unknown due to model simplifications and omissions. Error-domain model falsification reveals properties of a structure when uncertainty dependencies are unknown. Comparison with residual minimization technique and Bayesian inference.
uncertainties dependencies falsification bayesian system identification