Bayesian Compendium 2nd Edition
English | 2024 | 978-3-031-66085-6 | 262 pages| Epub PDF (True) | 33 MB
Aiming to demystify the approach, it explains how to parameterize and compare models while accounting for uncertainties in data, model parameters and model structures. The literature offers a bewildering variety of techniques (Bayesian calibration, data assimilation, Kalman filtering, model-data fusion, .).
