An enhanced least squares method for regression models with unidentified weighting factors
Manfred Wiessner, Benoît Loridant, Paul Angerer, Martin Medebach, Ewald Werner, Ernst Gamsjäger
This work introduces a novel Bayesian inspired regression method for the simultaneous estimation of model parameters and data uncertainties. The key mathematical result of this framework is an extended least squares objective function.