Amy in Randomland [book review]

Amy’s Luck is a short book by David Hand that I recently received for review in CHANCE. David, whom I have known for quite a while now, is professor at Imperial College London. This is not his first book, by far! But this may be the most unusual one, if not the shortest. Written as a pastiche of Alice’s Adventures in Wonderland, it tells of the adventures of a young girl named Amy in the pursuit of luck or at least of its meaning. It has about the same number of chapters as Carroll’s book and could easily be read on a leisurely boat trip from Oxford to Godstow. While non-sensical and playing on the imprecision of the English language, its probabilist is both correct and rational. References to the original Alice abound and I presumably missed a fair portion of them, having read Alice (in French) decades ago. The book also contains illustrations from the author, gathered into a charm bracelet printed on the cover and a most helpful appendix where David points out the real world stories behind those of Amy, which is also full of gems, like Kolmogorov being a train conductor in his youth. (Missing an addition about Galton’s quincunx, esp. when his cousin Darwin is more than mentioned.) Or Asimov creating the milihelen to measure how much beauty was required to launch a ship. Overall, it is quite charming and definitely enjoyable, if presumably not accessible by the same audience as Alice‘s. And unlikely to take over Alice‘s! But from “She could understand the idea that coins had heads”, to a Nightingale rose renamed after Miss Starling, to the permutation of Brown, Stein, and Bachelier into Braun, Stone, and a bachelor, David must have had fun writing it. As others will while reading it and trying to separate probabilistic sense from non-sense.

[Disclaimer about potential self-plagiarism: this post or an edited version will eventually appear in my Book Review section in CHANCE.]

simulating the pandemic

Nature of 13 November has a general public article on simulating the COVID pandemic as benefiting from the experience gained by climate-modelling methodology.

“…researchers didn’t appreciate how sensitive CovidSim was to small changes in its inputs, their results overestimated the extent to which a lockdown was likely to reduce deaths…”

The argument is essentially Bayesian, namely rather than using a best guess of the parameters of the model, esp. given the state of the available data (and the worse for March). When I read

“…epidemiologists should stress-test their simulations by running ‘ensemble’ models, in which thousands of versions of the model are run with a range of assumptions and inputs, to provide a spread of scenarios with different probabilities…”

it sounds completely Bayesian. Even though there is no discussion of the prior modelling or of the degree of wrongness of the epidemic model itself. The researchers at UCL who conducted the multiple simulations and the assessment of sensitivity to the 940 various parameters found that 19 of them had a strong impact, mostly

“…the length of the latent period during which an infected person has no symptoms and can’t pass the virus on; the effectiveness of social distancing; and how long after getting infected a person goes into isolation…”

but this outcome is predictable (and interesting). Mentions of Bayesian methods appear at the end of the paper:

“…the uncertainty in CovidSim inputs [uses] Bayesian statistical tools — already common in some epidemiological models of illnesses such as the livestock disease foot-and-mouth.”

and

“Bayesian tools are an improvement, says Tim Palmer, a climate physicist at the University of Oxford, who pioneered the use of ensemble modelling in weather forecasting.”

along with ensemble modelling, which sounds a synonym for Bayesian model averaging… (The April issue on the topic had also Bayesian aspects that were explicitely mentionned.)

the exponential power of now

The New York Times had an interview on 13 March with Britta Jewell (MRC, Imperial College London) and Nick Jewell (London School of Hygiene and Tropical Medicine & U of C Berkeley), both epidemiologists. (Nick is also an AE for Biometrika.) Where they explain quite convincingly that the devastating power of the exponential growth and the resulting need for immediate reaction. An urgency that Western governments failed to heed, unsurprisingly including the US federal government. Maybe they should have been told afresh about the legend of paal paysam, where the king who lost to Krishna was asked to double rice grains on the successive squares of a chess board. (Although this is presumably too foreign a thought experiment for The agent orange. He presumably prefers the unbelievable ideological rantings of John Ioannides. Who apparently does mind sacrificing “people with limited life expectancies” for the sake of the economy.) Incidentally, I find the title “The exponential power of now” fabulous!

lecturer position in Data Centric Engineering and Statistics, Imperial College London

My friend and Warwick colleague Mark Girolami sent me this announcement for a permanent Lecturer position at Imperial [College London], funded by his recent research chair by the Royal Academy of Engineering (congrats, Mark!). Deadline is April 13, so hurry up!!!

 

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.