Four short links: 1 July 2019

General-Purpose Probabilistic Programming, Microsoft's Linux, Decolonizing Data, Testing Statistical Softwares

1. Gen -- general-purpose probabilistic programming system with programmable inference. Julia package described as Gen's flexible modeling and inference programming capabilities unify symbolic, neural, probabilistic, and simulation-based approaches to modeling and inference, including causal modeling, symbolic programming, deep learning, hierarchical Bayesian modeling, graphics and physics engines, and planning and reinforcement learning..
2. WSL2 Linux Kernel -- source for the Linux kernel used in Windows Subsystem for Linux 2 (WSL2).
3. Decolonizing Data -- Decolonizing data means that the community itself is the one determining the information they want us to gather. Why are we gathering it? Who's interpreting it? And are we interpreting it in a way that truly serves our communities? Decolonizing data is about controlling our own story and making decisions based on what is best for our people. That hasn't been done in data before, and that's what's shifting and changing.
4. Testing Statistical Software -- In this post, I describe how I evaluate the trustworthiness of a modeling package, and in particular what I want from the test suite. If you use statistical software, this post will help you evaluate whether a package is worth using. If you write statistical software, this post will help you confirm the correctness of the code that you write.

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