Archive for Jean-Michel Marin

Monsieur le Président [reposted]

Posted in Books, Statistics, University life with tags , , , , , , , , , , , on April 11, 2020 by xi'an

Let us carry out screening campaigns on representative samples of population!

Mr President of the Republic, as you rightly indicated, we are at war and everything must be done to combat the spread of CODIV-19. You had the wisdom to surround yourself with a Scientific Council and an Analysis, Research and Expertise Committee, both competent, and, as you know, applied mathematicians, statisticians have a role to play in this battle. Yes, to predict the evolution of the epidemic, mathematical models are used at different scales. This allows us estimate the number of people infected in the coming weeks and months. We are at war and these predictions are essential to the development of the best control strategy. They inform political decisions. This is especially with the help of these items of information that the confinement of the French population has been decided and renewed.

Mr President we are at war and these predictions must be the most robust possible. The more precise they are, the better the decisions they will guide. Mathematical models include a number of unknown parameters whose values ​​should be set based on expert advice or data. These include the transmission rate, incubation time, contagion time, and, of course, to initialize dynamic mathematical models, the number of covered individuals. To enjoy more reliable predictions, it is necessary to better estimate such crucial quantities. The proportion of healthy carriers appears to be a particularly critical parameter.

Mr President, we are at war and we must assess the proportions of healthy carriers by geographic areas. We do not currently have the means to implement massive screenings, but we can carry out surveys. This means, for a well-defined geographic area, to run biological tests on samples of individuals that are drawn at random and are representative of the total population of the area. Such data would come to supplement those already available and would considerably reduce the uncertainty in model predictions.

Mr. President, we are at war, let us give ourselves the means to fight effectively against this scourge. Thanks to a significant effort, the number of individuals that can be tested daily increases significantly, let’s devote some of these available tests to samples representative. For each individual drawn at random, we will perform a nasal swab, a blood test, let us collect clinical data and other items of information on its follow-up barriers. This would provide important information on the percentage of immunized French people. This data would open the possibility to feed mathematical models wisely, and hence to make informed decisions about the different strategies of deconfinement.

Mr. President, we are at war. This strategy, which could at first be deployed only in the most affected sectors, is, we believe, essential. It is doable: designing the survey and determining a representative sample is not an issue, going to the homes of the people in the sample, towards taking samples and having them fill out a questionnaire is also perfectly achievable if we give ourselves the means to do so. You only have to decide that a few of the available PCR tests and serological tests will be devoted to these statistical studies. In Paris and in the Grand Est, for instance, a mere few thousand tests on a representative population of individuals properly selected could better assess the situation and help in taking informed decisions.

Mr. President, a proposal to this effect has been presented to the Scientific Council and to the Analysis, Research and Expertise Committee that you have set up by a group of mathematicians at École Polytechnique with Professor Josselin Garnier at their head. You will realise by reading this tribune that the statistician that I am does support very strongly. I am in no way disputing the competence of the councils which support you but you have to act quickly and, I repeat, only dedicate a few thousand tests to statistics studies. Emergency is everywhere, assistance to the patients, to people in intensive care, must of course be the priority, but let us attempt to anticipate as well . We do not have the means to massively test the entire population, let us run polls.

Jean-Michel Marin
Professeur à l’Université de Montpellier
Président de la Société Française de Statistique
Directeur de l’Institut Montpelliérain Alexander Grothendieck
Vice-Doyen de la Faculté des Sciences de Montpellier

a typo that went under the radar

Posted in Books, R, Statistics, University life with tags , , , , , , , on January 25, 2017 by xi'an

A chance occurrence on X validated: a question on an incomprehensible formula for Bayesian model choice: which, most unfortunately!, appeared in Bayesian Essentials with R! Eeech! It looks like one line in our LATEX file got erased and the likelihood part in the denominator altogether vanished. Apologies to all readers confused by this nonsensical formula!

The Grothendieck papers

Posted in Books, Kids, Mountains, pictures, University life with tags , , , , , , , , on December 28, 2016 by xi'an

Running back towards Carnon, along the expressway (!), with pink flamingoes in the distance, June 15, 2012Following the death of the mathematician Alexandre Grothendieck in 2014, his former maths department at the University of Montpellier decided to digitise in very high resolution the 28,000 pages of notes he had left to the department. Under the supervision of Jean-Michel Marin, Head of the said department! However, thanks to the French laws governing succession, those notes cannot be posted on-line without the authorisation of the five children of Grothendieck, who keep a moral right on those notes, even though they were given to the department. Grothendieck’s children want to recover all their father’s notes—which amount to more than 90,000 handwritten pages—presumably towards a bulk sale to a prestigious American university, but the succession is in limbo while the monetary value of those notes is not ascertained. And the digitised notes are stuck in this legal no man’s land as well. It is fairly ironical that those notes are at the centre of a financial conundrum, when Grothendieck’s anarchist principles led him to refuse awards and positions and to lead a recluse and frugal life in an isolated mountain village. And to prohibit the publication of those notes… Jean-Michel remains confident though that a solution can soon be reached between Grothendieck’s children, the University, the IHES, and the French National Library. I hope those notes can be made public, so that anyone could consult them. In paper or digitised format. Even though most of these pages may just be unexploitable. But at least they will be available rather than stuck in a storage for another 25 years.

Bayesian Essentials with R [book review]

Posted in Books, R, Statistics, University life with tags , , , , , , , on July 28, 2016 by xi'an

[A review of Bayesian Essentials that appeared in Technometrics two weeks ago, with the first author being rechristened Jean-Michael!]

“Overall this book is a very helpful and useful introduction to Bayesian methods of data analysis. I found the use of R, the code in the book, and the companion R package, bayess, to be helpful to those who want to begin using  Bayesian methods in data analysis. One topic that I would like to see added is the use of Bayesian methods in change point problems, a topic that we found useful in a recent article and which could be added to the time series chapter. Overall this is a solid book and well worth considering by its intended audience.”
David E. BOOTH
Kent State University

amazing Gibbs sampler

Posted in Books, pictures, R, Statistics, University life with tags , , , , , , on February 19, 2015 by xi'an

BayesmWhen playing with Peter Rossi’s bayesm R package during a visit of Jean-Michel Marin to Paris, last week, we came up with the above Gibbs outcome. The setting is a Gaussian mixture model with three components in dimension 5 and the prior distributions are standard conjugate. In this case, with 500 observations and 5000 Gibbs iterations, the Markov chain (for one component of one mean of the mixture) has two highly distinct regimes: one that revolves around the true value of the parameter, 2.5, and one that explores a much broader area (which is associated with a much smaller value of the component weight). What we found amazing is the Gibbs ability to entertain both regimes, simultaneously.