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 quomodocumque.wordpress.com
Subriemannian parallel parking on the Heisenberg group | Quomodocumque
| | hadrienj.github.io
Introduction to diagonal and symmetric matrices, unit and orthogonal vectors using Python/Numpy examples and drawings
3.6 parsecs away

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| | In this post, we will see special kinds of matrix and vectors the diagonal and symmetric matrices, the unit vector and the concept of orthogonality.
| | gereshes.com
An Introduction to Stability
5.7 parsecs away

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| | This post is focused on presenting the basics of stability for dynamical systems, and answers what will our system do if we perturb it a small amount?
| | austinmorlan.com
Deriving the 3D Rotation Matrix - Austin Morlan
5.6 parsecs away

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| | It took me longer than necessary to understand how a rotation transform matrix rotates a vector through three-dimensional space. Not because it's a difficult concept but because it is often poorly explained in textbooks. Even the most explanatory book might derive the matrix for a rotation around one axis (e.g., x) but then present the other two matrices without showing their derivation. I'll explain my own understanding of their derivation in hopes that it will enlighten others that didn't catch on right away.
| | thomvolker.github.io
Different ways of calculating OLS regression coefficients (in R) - Thom Volker
35.4 parsecs away

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| Many different ways of calculating OLS regression coefficients exist, but some ways are more efficient than others. In this post we discuss some of the most common ways of calculating OLS regression coefficients, and how they relate to each other. Throughout, I assume some knowledge of linear algebra (i.e., the ability to multiply matrices), but other than that, I tried to simplify everything as much as possible.