Anticlustering is a method to divide a set of objects into groups, while ensuring that the different groups are similar to each other. One example would be to divide a cohort of students into school classes, and the different classes should be similar on demographic composition, gender, and maybe previous grades. Ever since I implemented the openly available anticlust #rstats package, I realized that there is a wide range of different applications, which I had not thought of before.

I guess now is a good time to start posting more on Mastodon, and provide a (re)introduction. I will mostly post on the #rstats tag, and I believe it is awesome if the community can find a place to stay on here. I am a researcher at Heinrich Heine University Düsseldorf at the Department of Psychology. I am interested in programming, statistics and optimization. My most dear #rstats project is the anticlust package (https://github.com/m-Py/anticlust), which implements the method of anticlustering.

Hello, good people!

I've come again with another appeal for your help. Please, if you know or are aware of any openings for global remote R developer roles, be it in data science, analytics, or visualization, kindly pass them my way; it would mean a whole lot to me at this point.

I have been out of job for 6 months now and the ride has been very rough. Therefore, I am pleading for your assistance to help me get my next job, please. 🙏

#rstats #datascience #dataanalytics #dataviz