Sensitivity analysis and Bayesian calibration for testing robustness of the BASGRA model in different environments

Sensitivity analysis and Bayesian calibration for testing robustness of the BASGRA model in... •The parameters to be fixed were consistent across sites.•Model calibration must be performed separately for each specific case.•Possible to reduce model parameters from 66 to 45.•Strong model reductions must be avoided.•The error term for the training data were characterised by timing (phase shift). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ecological Modelling Elsevier

Sensitivity analysis and Bayesian calibration for testing robustness of the BASGRA model in different environments

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier B.V.
ISSN
0304-3800
eISSN
1872-7026
D.O.I.
10.1016/j.ecolmodel.2017.05.015
Publisher site
See Article on Publisher Site

Abstract

•The parameters to be fixed were consistent across sites.•Model calibration must be performed separately for each specific case.•Possible to reduce model parameters from 66 to 45.•Strong model reductions must be avoided.•The error term for the training data were characterised by timing (phase shift).

Journal

Ecological ModellingElsevier

Published: Sep 10, 2017

References

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