Pausal Živference @PausalZ@qoto.org

To celebrate the v1.0 release, I wrote up a short guide on how to implement GAMs with `delicatessen`

https://github.com/pzivich/Delicatessen/blob/main/examples/Generalized-Additive-Model.ipynb

v1.0 of `delicatessen` is now available 🎊

https://pypi.org/project/delicatessen/1.0/

The biggest change is changes to supported versions of Python (now 3.8-3.11) and version dependencies on SciPy and NumPy. These changes allow for much faster computation times

Other changes include the planned syntax change for regression models. The legacy versions are no longer available

I feel pretty dumb for not realizing that GAMs are really just penalized regression with some automatically generated splines

Like I've been doing GAMs 'by-hand' for years now....

@kdpsingh what are your top 3 favorite features compared to others?

a part of my brain has slowly become devoted to thinking of funny software package names

@ct_bergstrom they say diagnosed with Covid-19, which would imply the CFR

also I think the risk of transmission piece is more problematic information then their 3%...

Delighted to share my book chapter on machine learning and causal inference now available in Wiley StatsRef

https://onlinelibrary.wiley.com/doi/full/10.1002/9781118445112.stat08412

@wzbillings thanks!

Does base R just not have a forward fill function?

there are two wolves inside me

@willball12 I mean it depends what you want to do. If you want to get into machine learning, python has far better support. There are a few syntax items that I think make python better (but that is all subject to opinion)

I don't think it was recorded, but here are some slides on why to use python I presented this past August

https://github.com/pzivich/Presentations/blob/master/ISCB43/Zivich_Python_ISCB43.pdf

also because I support open-source bullshit, all the code is here https://github.com/pzivich/RNN-Abstract-Generator

so you can train it on another topic if you want (should only take a few hours)

Lots of discussion of #ChatGPT but I already created a bullshit scientific abstract generator

https://threadreaderapp.com/thread/1412920545411227648.html

@jebyrnes yeah I made it (but not the meme format obviously), feel free to include in your lecture

@healthstatsdude the same story as applied math tbh

#EpiVerse

@Tim_P_Morris @MiguelHernan I think it is related to Lin & Wei 1989 (which I think you could also use their variance estimator instead of the bootstrap)

Lin DY & Wei LJ. (1989). The robust inference for the Cox proportional hazards model. JASA, 84(408), 1074-1078.

no penalty would be a diagonal line with a slope of 1