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Programming Leftovers
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Brad Taunt ☛ The Forge Wars
The problem is that some developers will shame you for using GitHub, some will disagree with Codeberg’s ToS, and others will complain about Sourcehut’s email-based workflow. It’s impossible to make every user happy. Such is life, I guess.
So, I’ve decided to say “screw it” and started hosting my own git instance running on top of cgit. You can check it out here: git.btxx.org
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Murage Kibicho ☛ How GCC Eliminates Unnecessary Integer Division
The number field sieve demands us perform repetitive divisibility tests. Observe that GCC runs faster when provided a constant divisor, not a variable, as shown below.
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NLNet Foundation ☛ Maintaining the love for coding in the time of AI
I want to take a step back and explain how we maintain open-source projects that are intended to run in critical infrastructure. Because when people think of open-source, they almost automatically assume that there is a community of individual developers collaborating on a project.
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Perl / Raku
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Arne Sommer ☛ Median Box with Raku - Arne Sommer
This is my response to The Weekly Challenge #391.
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R / R-Script
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Rlang ☛ Bootstrap v traditional asymptotic normal assumptions by @ellis2013nz
Today’s just a very short sequel to last week’s post, where I had a look at some very skewed distributions to test the idea that sample sizes sometimes need to be in the tens of thousands for the sample mean to have a normal distribution.>
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Free Range Statistics ☛ Bootstrap v traditional asymptotic normal assumptions
Bias-corrected and adjusted bootstrap does an ok job at confidence intervals of the mean from some example skewed distributions. Better than does relying on the traditional methods of just assuming normality from the central limit theorem. But for particularly awkward distributions, sample sizes are still needed in the thousands to get coverage that resembles the claimed coverage.
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