EFS is the Extended Fellner Schall smoothness selection method that Simon & Matteo Fasiolo developed, & which was initially used for the twlss() family

EFS is neat bc it doesn't require all the fancy higher order derivatives of model quantities to fit the model, even for location scale families

Why is scasm() such a big deal? Natalya Pya & Simon did some work leading to Natalya's *scam* 📦 with a load of different shape constraints. But the algorithm was GCV-based and only worked for the standard families.

scasm() works for *any* family in mgcv thanks to EFS & just slots into models

The full change log with all the changes is here: cran.r-project.org/web/packages...

I've already started the process of getting these new features supported in the gratia 📦. Shape constraint smooths mostly just work; small fix was needed bc structure of the smooths lacked something gam() produces

🌟 plot.gam() also has a new theme: scheme=2

This draws plots with 68 & 95% intervals (by default) and has a ggplot2-like grey plot background

🌟 plot.gam() gains a deriv argument, which if TRUE plots derivatives of univariate smooths instead of the usual partial effect plots

Partial effect plots can be confusing. With deriv=TRUE you see the change in Y (η) for a small change in X, which is comparable with usual interpretations of model 𝛽

🌟 New family, bcg(), for (censored) Box-Cox Gaussian responses (basically anything that is conditionally Gaussian *after* a Box-Cox transform of Y_i)

Feel free to tag me on any questions if you post them here. Lots of answers on CrossValidated in the generalized additive model tag cover HGAMs. If you have a stats question you could also ask it there

I have very fond memories of feeding the giraffe there; have fun enjoying Nairobi (taking breakfast at the national park at dawn, in one of the picnic / viewpoints on the high ground overlooking the rest of the park was a real treat, as was the elephant orphanage)

If you want to check out the examples from the Physalia course, the materials from the last running are available on GitHub

github.com/gavinsimpson...

I’d be happy to add/use a psych example or two if you have suggestions for papers or analyses where the data are open?

As I’m a geographer by PhD working in ecology, environmental science, and now animal science, the examples tend towards the natural and life sciences, but they are quite varied so attendees from a wide array of backgrounds usually find them relatable.

I’ll be running a 3-day one at AU Viborg (about an hour from Aarhus, Denmark) June 9th through 11th that is in person. Dates are TBC but registration should be open in the next couple of weeks

I’m also running an online one with @physaliacourses.bsky.social in December this year.

Congratulations Thomas; I know this release hasn’t been an easy one