I use one-at-a-time sensitivity analysis all the time, but it’s not without it’s dangers. It looks like developers are ahead of the statisticians in useful illustrative examples.
- Abuse of climate scientists on social media
- Constraining the carbon cycle in a land surface model – a talk for EGU23
- Communicating climate science through social media
- Communicating climate change through social media
- Uncertainty quantification and exascale computing in climate science
- Climate science in 10 minutes
- Visualising input spaces using emulators
- Visualising weird input spaces
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Climate scientist and statistician at the Met Office Hadley Centre.
[…] last week’s post, I thought it might be useful to have some practical examples of how to do sensitivity analysis […]
I am trying to implement OAT in R using the sensitivity package. I am loading the parameters by specifying ranges and steps to function: morris. When I feed parameters in this way, I have to assume that all parameter combinations in that range are meaningful. However, in my experiment, there are some forbidden parameter combinations and I want to exclude them (for eg: parameter1 must always be greater than parameter 2). Could you please let me know how that can be done?