Comments (1)
If you have a by
statement, e.g. s(phos, by = loc)
then you will get smooths for each location. You can also use the factor smooth approach, which basically treats it like a random slope for each location as in a mixed model. That is, you don't need separate models, just one that allows the effect to vary by location. Otherwise your models aren't really comparable as they are fit to different data. And while the approach just mentioned will give you statistical results, you'd probably do better just comparing AIC with the model with and without the by
approach.
Also, I don't mind answering questions if I can, but if you would, please reserve github issues for something specific to the doc (e.g. typos, code problem, etc.). I'm going to go ahead and close this as it's not specific to the document.
Glad you're finding the doc useful!
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Related Issues (14)
- update with stars HOT 1
- cleanup for mixed model comparison in appendix
- References section issues
- Reference to your .css file in another project HOT 1
- document display errors HOT 1
- add bit from Shalizi HOT 1
- Switch to bookdown HOT 1
- demonstrate first derivative
- time series
- change table format HOT 1
- change visreg to ggeffects
- change glm formulation in intro
- add big data section to appendix
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