In this episode, I dived into non-normal distributions, went from rags to ridges, rode the Python Language Summit lightning, and looked at the ‘GenericML’ package.

References:

Covsim: An R package for Simulating Non-Normal Data for Structural Equation Models Using Copulas
Rags2ridges: A One-stop-L2-shop for Graphical Modeling of High-Dimensional Precision Matrices
Transmissibility in Interactive Nanocomposite Diffusion: The Nonlinear Double-Diffusion Model
Editorial: Modelling collective motion across scales
The Application of the Functional Variable Method for Solving the Loaded Nonlinear Evaluation Equations
The derivative of the determinant of a matrix
Python 3.11.0b1 is now available
The 2022 Python Language Summit: Upstreaming optimisations from Cinder
The 2022 Python Language Summit: Performance Improvements by the Faster CPython team
The 2022 Python Language Summit: Python in the browser
The 2022 Python Language Summit: A per-interpreter GIL
The 2022 Python Language Summit: Achieving immortality
Fiducial Inference: Fisher’s Great Failure
Beta Distribution: Uses, Parameters & Examples
Geometric Distribution: Uses, Calculator & Formula
Alignment cheatsheet
5 Key Data Visualization Principles Explained – Examples in R
Three packages that port the tidyverse to Python
How to embed a Shiny app into your blog posts


R  packages:

biogeom: Biological Geometries
GenericML: Generic Machine Learning Inference
PMA2:  Penalized Multivariate Analysis

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