Dagmar Fraser @dagmarfraser.bsky.social

🎉 New paper alert! 🧠 The velocity-curvature power law is one of the 'kinematic laws of nature' (Flash 2021), a 'fundamental law of human control' (Zago et al. 2016), and one of the 'kinematic regularities' (Frith & Frith 2023) thought to underlie all biological motion. 1/9

@cchapman You can even add the necessary packages without ever looking at R system('Rscript -e "install.packages(''psych'', repos=''cran.r-project.org'')"') system('Rscript -e "install.packages(''ICC'', repos=''cran.r-project.org'')"') #MATLAB #MATLABambassador #R

@cchapman Slight overhead of launching R every time you do that Rscript system call!

Follow-up to my ICC thread from last week 🧵 I wanted to test Salarian's MATLAB FileExchange code. Thanks to @cchapman.bsky.social for pointing me toward R. I took it further than perhaps intended.

What is social cognition? Watch my interview with Drs. Uta Frith (@utafrith) and Chris Frith about their book, “What Makes Us Social?” #Psychology #Science youtu.be/1I2LvEFKhe8

So here’s the question: what’s your ICC workflow? There must be dozens of us! Dozens! MATLAB, R, Python… or do you still cling to SPSS? 🧐 #MATLAB #MATLABambassador

But… last updated in 2016. How far do we trust “random” code? 🤔 I will havw to write some tests. This is the reality of (apparently!) niche stats in MATLAB, community-driven, not MathWorks-authored. Who do I have to bribe to get it added?

New experience today 🎓: I set up an experiment to check the test–retest stability of my favourite kinematic measure: Lacquaniti’s 1/3 power law. A velocity–curvature relationship that results in a kinematic invariance which might underlie all biological motion.

Available on MATLAB Online– just click that Launch button on GitHub. 🚀 You don’t even need a license - 20hrs/month free! #MATLAB #PCA #KarhunenLoeve #MATLABambassador

🙏 It lets you: • Manipulate μ and σ of up to 3 variables • Adjust correlations • Watch Principal Components (PCs) emerge in real-time ⚡You can rotate 3D plots 🔄, click individual points to see their deviation vectors animated, and visualize projections onto each PC.

🧵 Back in 1999, I was hand-rolling the Karhunen-Loève transform using eig() … you may know it as Principal Component Analysis, or as the cool kids now know it by its rapper name PCA. 🎤 I had no fancy toolboxes with the pca() command.