I just released an update to OptimalTransportNetworks.jl (github.com/OptimalTrans...) providing performance improvements through hand-coded gradients and hessians. I also published a new web-application – the Transport Network Optimizer – available at otn.sebastiankrantz.com. #Julialang #DataScience

The article on "collapse: Advanced and Fast Statistical Computing and Data Transformation in R" has now been published (open-access) in the Journal of Statistical Software: www.jstatsoft.org/article/view... #rstats #DataScience

Recording of my talk on {collapse} and the {fastverse} at the Bank of Portugal‘s workshop „Speeding up Empirical Research: Tools and Techniques for Fast Computing“ in December is now online: www.youtube.com/watch?v=qO5d... It includes examples from trade and network processing. #rstats #DataScience

collapse and fastverse: Advanced and Fast Statistics and Data Transformation in R

YouTube video by Banco de Portugal

youtube.com

I’m thrilled to introduce flownet (sebkrantz.github.io/flownet/), a new R package for transport modeling, supporting stochastic or deterministic traffic assignment to large networks, and powerful tools for (multimodal) network processing/simplification: sebkrantz.github.io/Rblog/2026/0... #Rstats

Transport Modeling in R

High-performance tools for transport modeling - network processing, route enumeration, and traffic assignment in R. The package implements the Path-Sized Logit model for traffic assignment - Ben-Akiva...

sebkrantz.github.io

arXiv📈🤖 Fast and user-friendly econometrics estimations: The R package fixest By Berg\'e, Butts, McDermott

I'm excited to share the release and rOpenSci publication of dfms 1.0 (docs.ropensci.org/dfms), a high-performance, feature-rich implementation of Dynamics Factor Models for R, supporting mixed-frequency estimation and news decomposition for nowcasting. See also blog post: sebkrantz.github.io/Rblog/

Dynamic Factor Models for R

Efficient estimation of Dynamic Factor Models using the Expectation Maximization (EM) algorithm or Two-Step (2S) estimation, supporting datasets with missing data and mixed-frequency nowcasting applic...

docs.ropensci.org

I've started a new personal blog focused on research, career reflections, and travel experiences. The first post documents my recent 6-week trip through Southern Africa, from Zanzibar to Cape Town by Public Transport. FYI, enjoy! sebkrantz.github.io/blog/posts/f...

Version 0.3.0 of the {dfms} package for dynamic factor modelling in R just made it to CRAN, adding support for monthly + quarterly mixed frequency estimation. This allows for easy business cycle indicator estimation. More at sebkrantz.github.io/dfms/article... and sebkrantz.github.io/dfms/. #rstats

{collapse} 2.1.0 is out! It introduces a new fslice() function (sebkrantz.github.io/collapse/ref...), a new theory-consistent weighted quantile algorithm (sebkrantz.github.io/collapse/ref...) with excellent properties. And some convenience features such as join requirements: #rstats #DataScience

Feel free to join the ECA webinar if you want to see some crazy continent-scale spatial economic modelling. 📅 Feb 10 | 14:00-15:30 EAT Join industry experts as we explore the costs, benefits, and solutions for Africa’s infrastructure development. 🌐💡 🔗 Register now: bit.ly/3PWKynU

The {collapse} (@rcollapse.bsky.social) arXiv paper has just been updated - following extensive revision: arxiv.org/abs/2403.05038. I believe it is a great resource for anyone doing scientific computing with #rstats.

collapse: Advanced and Fast Statistical Computing and Data Transformation in R

collapse is a large C/C++-based infrastructure package facilitating complex statistical computing, data transformation, and exploration tasks in R - at outstanding levels of performance and memory eff...

arxiv.org

It's nice to see an increasing number of #rstats packages use {collapse}. A developer focused vignette was long planned and now it is here - with modest advice on writing efficient R package code in general and using {collapse} in particular: sebkrantz.github.io/collapse/art...