Author Archives: drewancameron

Over-confidence in Bayesian analyses of galaxy rotation curves …

Yesterday I had a ‘Matters Arising’ in Nature Astronomy published (non-paywalled shareable link here) on the topic given as the title of this blog post; with co-authors, Michael Burgess & Garry Angus.  Aside from identifying some particular technical issues with … Continue reading

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Code for causal inference: Interested in astronomical applications

Oxford PhD student, Rohan Arambepola, from the Malaria Atlas Project has today arXived a manuscript describing his investigation of the potential for causal feature selection methods to improve the out-of-sample predictive performance of geospatial (or really, “geospatiotemporal”?!) models fitted to … Continue reading

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[Link] A toast to the error detectors …

This.

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Non non Gaussian processes …

I noticed an interesting paper arXived just before Xmas proposing to model stellar spectra as “sparse, data-driven non-Gaussian processes”.  The non-Gaussian part is explained to mean that because a prior is placed on the covariance function and various hyper-parameters, when … Continue reading

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Boxing to watch on boxing day …

I realise that the origin of the holiday name is not the sport, but it’s a great chance to catch up on two fight of the year contenders, both coming out of the World Boxing Super Series program (both available … Continue reading

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RDT to Microscopy conversion is neither trivial nor unimportant …

A common criticism of malaria mapping work that I’ve been involved with runs to the effect that we don’t do the right thing when we correct for the difference between rapid diagnostic test (RDT) estimates of parasite prevalence and microscopic … Continue reading

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Astronomers invented Bayesian optimisation in 2019 …

Long time readers of this blog will know that I’ve been bigging up the potential of Bayesian optimisation approaches for fitting expensive astronomical simulations for many years now.  In particular, when likelihood function computations are computationally very expensive and possibly … Continue reading

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