MDBs Versus MIBs in Case of Multiple Hypotheses: A Study in Context of Deformation Analysis

Abstract Statistical testing procedures employed in geodetic quality control often consist of two steps: detection and identification. In the step, null hypothesis (working model) $$\mathcal {H}_0$$ ℋ 0 undergoes a validity check. If outcome step is rejection , identification potential source model error exercised through search among specified alternative hypotheses. The performance thus not only led by its ability to detect biases but correctly identify them as well. capability regime usually assessed Minimal Detectable Bias (MDB) given certain correct probability. information provided MDB concerns should be evaluated Identifiable (MIB) this contribution, we demonstrate difference between MIB. It hereby highlighted that small (or high probability detection) does necessarily imply MIB identification). factors driving are illustrated using simple example. Our analysis then continued framework deformation monitoring.