we have never been unable to develop a reliable predictive model

An alarming entry in The Guardian about the huge proportion of councils in the UK using machine-learning software to allocate benefits, detect child abuse or claim fraud. And relying blindly on the outcome of such software, despite their well-documented lack of reliability, uncertainty assessments, and warnings. Blindly in the sense that the impact of their (implemented) decision was not even reviewed, even though a portion of the councils does not consider renewing the contracts. With the appalling statement of the CEO of one software company reported in the title. Blaming further the lack of accessibility [for their company] of the data used by the councils for the impossibility [for the company] of providing risk factors and identifying bias, in an unbelievable newspeak inversion… As pointed out by David Spiegelhalter in the article, the openness should go the other way, namely that the algorithms behind the suggestions (read decisions) should be available to understand why these decisions were made. (A whole series of Guardian articles relate to this as well, under the heading “Automating poverty”.)

research position in Bristol

Christophe Andrieu is seeking a senior research associate (reference ACAD103715) at the University of Bristol to work on new approaches to Bayesian data science. The selected candidate would work with Prof. Christophe Andrieu (School of Mathematics) and Prof. Mark Beaumont (Life Science) on new approaches to tackle Bayesian inference in complex statistical models arising in particular in the area of Health Science, with a focus on genetics and/or epidemiological aspects. The position is associated with a £3M programme funded by EPSRC, Bayes4Health, and brings together research groups from the Universities of Lancaster, Bristol, Cambridge, Oxford and Warwick. Active collaboration across the partner institutions, other project partners and the programme grant CoSInES is expected. The position is for up to four years.

The position is for a duration of four years and interviews will take place in early October. Applicants with strong methodological and computational skills and are looking to put together a team of researchers with skills that cover theoretical, methodological and applied statistics should contact Christophe Andrieu at the earliest.

p-values, Bayes factors, and sufficiency

Among the many papers published in this special issue of TAS on statistical significance or lack thereof, there is a paper I had already read before (besides ours!), namely the paper by Jonty Rougier (U of Bristol, hence the picture) on connecting p-values, likelihood ratio, and Bayes factors. Jonty starts from the notion that the p-value is induced by a transform, summary, statistic of the sample, t(x), the larger this t(x), the less likely the null hypothesis, with density f⁰(x), to create an embedding model by exponential tilting, namely the exponential family with dominating measure f⁰, and natural statistic, t(x), and a positive parameter θ. In this embedding model, a Bayes factor can be derived from any prior on θ and the p-value satisfies an interesting double inequality, namely that it is less than the likelihood ratio, itself lower than any (other) Bayes factor. One novel aspect from my perspective is that I had thought up to now that this inequality only holds for one-dimensional problems, but there is no constraint here on the dimension of the data x. A remark I presumably made to Jonty on the first version of the paper is that the p-value itself remains invariant under a bijective increasing transform of the summary t(.). This means that there exists an infinity of such embedding families and that the bound remains true over all such families, although the value of this minimum is beyond my reach (could it be the p-value itself?!). This point is also clear in the justification of the analysis thanks to the Pitman-Koopman lemma. Another remark is that the perspective can be inverted in a more realistic setting when a genuine alternative model M¹ is considered and a genuine likelihood ratio is available. In that case the Bayes factor remains smaller than the likelihood ratio, itself larger than the p-value induced by the likelihood ratio statistic. Or its log. The induced embedded exponential tilting is then a geometric mixture of the null and of the locally optimal member of the alternative. I wonder if there is a parameterisation of this likelihood ratio into a p-value that would turn it into a uniform variate (under the null). Presumably not. While the approach remains firmly entrenched within the realm of p-values and Bayes factors, this exploration of a natural embedding of the original p-value is definitely worth mentioning in a class on the topic! (One typo though, namely that the Bayes factor is mentioned to be lower than one, which is incorrect.)

hittin’ a Brexit wall

postdoc position in London plus Seattle

Here is an announcement from Oliver Ratman for a postdoc position at Imperial College London with partners in Seattle, on epidemiology and new Bayesian methods for estimating sources of transmission with phylogenetics. As stressed by Ollie, no pre-requisites in phylogenetics are required, they are really looking for someone with solid foundations in Mathematics/Statistics, especially Bayesian Statistics, and good computing skills (R, github, MCMC, Stan). The search is officially for a Postdoc in Statistics and Pathogen Phylodynamics. Reference number is NS2017189LH. Deadline is April 07, 2018.

more positions in the UK [postdoc & professor]

I have received additional emails from England advertising for positions in Bristol, Durham, and London, so here they are, with links to the complete advertising!

1. The University of Bristol is seeking to appoint a number of Chairs in any areas of Mathematics or Statistical Science, in support of a major strategic expansion of the School of Mathematics. Deadline is December 4.
2. Durham University is opening a newly created position of Professor of Statistics, with research and teaching duties. Deadline is November 6.
3. Oliver Ratman, in the Department of Mathematics at Imperial College London, is seeking a Research Associate in Statistics and Pathogen Phylodynamics. Deadline is October 30.

position in Bristol

There is [also] an opening for a Lecturer or Senior Lecture or Reader at the University of Bristol, with deadline 27th of November, 2017. The School of Mathematics and in particular the Institute for Statistical Science are quite active in research, with top rankings and a rich area of expertise domains, while [based on personal experience] the City of Bristol is a great place to live! (Details through the links.)