A comparison of statistical emulation methodologies for multi-wave calibration of environmental models.

ABSTRACT: Expensive computer codes, particularly those used for simulating environmental or geological processes, such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power. This was the case for the a

SUBMITTER: Salter JM 

PROVIDER: S-EPMC5157755 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature