For researchers pushing the boundaries of scalable statistical modeling, the R-INLA framework is a cornerstone of daily computational work. We are excited to share that the official R-INLA project has officially launched a brand-new, modernized website.
About
A Centralized Resource for the Statistical Community
The redesigned platform offers a streamlined, user-friendly experience for both newcomers and seasoned practitioners. It serves as a comprehensive hub for official documentation, software updates, case studies, and advanced tutorials. The new site makes navigating the extensive INLA ecosystem easier than ever, providing a much-needed focal point for researchers utilizing approximate Bayesian methods.
Powering Our Group's Innovation
Within our own research team, the INLA methodology continues to be a vital engine for discovery. From developing specialized software packages for structural equation models to teaching advanced global short courses and building GPU-accelerated inference frameworks, we rely heavily on the robust foundation that R-INLA provides. This updated digital presence will be an invaluable resource not only for our ongoing projects but also for the students and international colleagues we collaborate with.
We encourage everyone in the computational statistics and data science communities to explore the new site at r-inla.org and bookmark it for future reference!
Related People
Esmail Abdul Fattah
- Postdoctoral Research Fellow, Statistics
