4.4. Proficiency — Modified Cloud Analysis

Theoretical Background

Proficiency combines efficiency with the predictability of the IM from seismic hazard analysis (Padgett et al., 2008). An IM may be efficient but difficult to predict via a ground-motion model (GMM), making it less practical for risk assessment.

Definition

Proficiency is defined as:

\[\zeta = \beta_{D|IM} \cdot \sigma_{\ln IM}\]

where \(\beta_{D|IM}\) is the efficiency (record-to-record dispersion of demand given IM) and \(\sigma_{\ln IM}\) is the total logarithmic standard deviation of the IM predicted by the GMM at the hazard level of interest (the “predictability” of the IM).

For MCA, \(\beta_{D|IM}\) is the residual standard deviation from the cloud regression evaluated at the DCR = 1 level.

A smaller \(\zeta\) indicates a more proficient IM — one that is both efficient and predictable.