Category Archives: Inference

Videos: Intro to Probability and Bayes for (Astro)physicists

In late 2017 I went to ESAC in Madrid to do a winter school teaching basic statistics things to astronomers. I’ve presented similar material twice before, but I think it was better this time since I’ve learned more and there … Continue reading

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R-based model specification for DNest4

Last night, I decided to bite the bullet and add yet another method to implement models in DNest4, this time using R. Statisticians know R, so it’s probably a good idea to support their language in some form. This brings … Continue reading

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Types and Jaynes’s ‘Mind Projection Fallacy’

Ed Jaynes frequently criticised what he called the mind projection fallacy. This is the implicit assumption that our concepts of, say, gaussianity, randomness, and so on, reflect properties of to be found “out there in nature”, whereas they often reside … Continue reading

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That’s not what I meant…

A lot of my research over the years has involved fitting images. Usually, I use the traditional assumption that the conditional prior for the data pixels given the model pixels is iid normal with mean zero. But in some cases … Continue reading

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Some software I’ve been working on

Hi everyone. I’ve recently been expanding my computational horizons and it has helped me to put some of my trans-dimensional Bayesian inference codes for astronomy into a more usable state for others, with configuration files in YAML, nonzero documentation (though … Continue reading

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DNest4 version 0.2.0

G’day everyone. This post is to update you on some work I’ve been doing (along with some collaborators, notably João Faria) on DNest4. So, you’ll likely only care if you’re a user of that package. There have been enough additions … Continue reading

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New video about overfitting

Recently I popped across the road to AUT to give a talk for their statisticians and applied mathematicians. In the Q&A session, I got asked about overfitting, and had the same experience I described in this old post. This motivated … Continue reading

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