Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy
<p>Bayesian inference of microbial soil respiration models is often based on the assumptions that the residuals are independent (i.e., no temporal or spatial correlation), identically distributed (i.e., Gaussian noise), and have constant variance (i.e., homoscedastic). In the presence of model...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-05-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/12/2009/2019/gmd-12-2009-2019.pdf |