Monthly Archives: March 2014

Six key trends in contemporary statistics that really could revolutionise astronomical data analysis …

(5) Big Data Bayes. A lot of fuss is made about “Big Data” and the need for new statistical analysis tools to help us cope with the challenges it represents, but again there’s little mention in the astronomical discussion to this … Continue reading

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Six key trends in contemporary statistics that really could revolutionise astronomical data analysis …

(4) ABC and the pseudo-marginal method. Of the six trends discussed here Approximate Bayesian Computation (ABC) is my personal favourite, in part because I’ve enjoyed applying it to estimation of Chlamydia incidence estimates in a recent Australian study with collaborators at the … Continue reading

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Six key trends in contemporary statistics that really could revolutionise astronomical data analysis …

(3) particle filters and population Monte Carlo. Nowadays more-or-less everyone in astronomy has heard of Markov Chain Monte Carlo (MCMC), and a substantial fraction of astronomers will have either run an MCMC chain themselves or at least coauthored a paper … Continue reading

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Six key trends in contemporary statistics that really could revolutionise astronomical data analysis …

(2) the SPDE approach to large-scale random fields. Cosmologists have long been familiar with the statistics of random fields, owing in part to the prominent role of the Gaussian and log-Gaussian in models of the initial density perturbations (Bardeen et … Continue reading

Posted in Astrostatistics, Gaussian Processes, Infinite-Dimensional Inference, INLA, Statistics | 3 Comments

Six key trends in contemporary statistics that really could revolutionise astronomical data analysis …

With all the schools (Canary Islands, Penn State), conferences (IAUS306; 2013: Astroinformatics), books (S,MD,&ML in Astronomy), and articles (e.g. Hilbe 2014) hyping the potential of contemporary statistical methodology for revolutionising the practice of astronomy and astronomical data analysis you’d be forgiven for … Continue reading

Posted in Astrostatistics, Dirichlet Processes, Statistics | 2 Comments

How science works …

There’s quite a song and dance made in science classes at school and university to the tune that the scientific process is superior to non-scientific processes of inference and belief because scientists are sceptical by nature, keen even to challenge … Continue reading

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Training the next generation of astrostatisticians …

I recently became aware, more-or-less simultaneously, of two new endeavours intended to teach Bayesian statistics to the next generation of astronomers—the 2014 Canary Islands Winter School and the new textbook by Ivezic et al., “Statistics, Data Mining, and Machine Learning … Continue reading

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