Dan Simpson • 3/21/2022

Sparse Matrices 1: The linear algebra of linear mixed effects models and their generalisations

Read Original

The article details a project to implement efficient Bayesian inference for linear mixed models and related models (like GAMs) by leveraging sparse linear algebra techniques, inspired by the INLA method. The author discusses prototyping this in Python using JAX to overcome scalability challenges in MCMC frameworks like Stan.

0 comments
#Python #linear algebra #sparse matrices
Sparse Matrices 1: The linear algebra of linear mixed effects models and their generalisations

Comments

No comments yet

Be the first to share your thoughts!

Browser Extension

Get instant access to AllDevBlogs from your browser

Top of the Week

1
Quoting Thariq Shihipar
Simon Willison • 2 votes
2
Using Browser Apis In React Practical Guide
Jivbcoop • 2 votes
3
Top picks — 2026 January
Paweł Grzybek • 1 votes
4
In Praise of –dry-run
Henrik Warne • 1 votes
5
Deep Learning is Powerful Because It Makes Hard Things Easy - Reflections 10 Years On
Ferenc Huszár • 1 votes
6
Vibe coding your first iOS app
William Denniss • 1 votes
7
AGI, ASI, A*I – Do we have all we need to get there?
John D. Cook • 1 votes
8
Dew Drop – January 15, 2026 (#4583)
Alvin Ashcraft • 1 votes