Description: The aim of this TG is to develop a manuscript or tutorial that summarizes the state-of-the-art and best practice for the (Bayesian) calibration of forest models. Topics that will be covered include
- Direct and indirect estimation of parameters, calibration philosophies, objective functions, the Bayesian framework
- Optimization algorithms and global samplers (MCMC)
- Model comparison and model averaging methods
- Quantification of parametric and predictive uncertainties
The final document is expected to have a strongly practical focus, with code examples etc., similar to the tutorial by Marcel van Oijen.
Participation: If you are interested in participating in the task group, please contact the task group coordinator directly. If you are interested in the working group in general, please contact the working group leaders.