## to bike or not to bike

Posted in Kids, pictures, Running, Travel with tags , , , , , , , , , on March 22, 2020 by xi'an

A recent debate between the candidates to the Paris mayorship, including a former Health minister and physician, led to arguments as to whether or not biking in Paris is healthy. Obviously, it is beneficial for the community, but the question is rather about the personal benefits vs dangers of riding a bike daily to work. Extra physical activity on the one hand, exposition to air pollution and accidents on the other hand. With an accident rate that increased during the recent strikes, but at a lesser rate (153%) than the number of cyclists in the streets of Paris (260%). While I do not find the air particularly stinky or unpleasant on my daily 25km, except in the frequent jams between Porte d’Auteuil and Porte de la Muette, and while I haven’t noticed a direct impact on my breathing or general shape, I try to avoid rush hours, especially on the way back home with a good climb near Porte de Versailles (the more on days when it is jammed solid with delivery trucks for the nearby exhibition centre). As for accidents, trying to maintain constant vigilance and predicting potential fishtails is the rule, as is avoiding most bike paths as I find them much more accident-prone than main streets… (Green lights are also more dangerous than red lights, in my opinion!) Presumably, so far at least, benefits outweight the costs!

## …place Dauphine…il est cinq heures, Paris s’éveille [jatp]

Posted in pictures, Travel, Wines with tags , , , , , , , , , , on November 21, 2019 by xi'an

## a chance (?) encounter

Posted in Kids, pictures, Travel with tags , , , , , on July 16, 2019 by xi'an

As I was cycling to Paris Dauphine, a few days ago, I spotted someone sitting on a bench and working on a laptop who suspiciously looked like… Andrew Gelman! As I knew Andrew was in Paris that week, and as we were reasonably close to Dauphine, this did not sound like a zero probability event. I thus stopped to check that indeed this was the real Andrew, who happened to be in the vicinity and had decided to run this double blind experiment as to whether or not we could spot one another. While I am reasonably aware of my surroundings when cycling (as a matter of mere survival), my radar rarely extends to people sitting on benches, especially when I am riding the middle white line on the boulevard. As I was further a wee bit late that day, I should have been in my office by the time Andrew sat there. A chance encounter, hence, or a super subjective inference from the author of BDA!

## Monte Carlo fusion

Posted in Statistics with tags , , , , , , , , , on January 18, 2019 by xi'an

Hongsheng Dai, Murray Pollock (University of Warwick), and Gareth Roberts (University of Warwick) just arXived a paper we discussed together last year while I was at Warwick. Where fusion means bringing different parts of the target distribution

f(x)∝f¹(x)f²(x)…

together, once simulation from each part has been done. In the same spirit as in Scott et al. (2016) consensus Monte Carlo. Where for instance the components of the target cannot be computed simultaneously, either because of the size of the dataset, or because of privacy issues.The idea in this paper is to target an augmented density with the above marginal, using for each component of f, an auxiliary variable x¹,x²,…, and a target that is the product of the squared component, f¹(x¹)², f²(x²)², … by a transition density keeping f¹(.)²,f²(.)²,… invariant:

$f^c(x^c)^2 p_c(y|x^c) / f_c(y)$

as for instance the transition density of a Langevin diffusion. The marginal of

$\prod_c f^c(x^c)^2 p_c(y|x^c) / f_c(y)$

as a function of y is then the targeted original product. Simulating from this new extended target can be achieved by rejection sampling. (Any impact of the number of auxiliary variables on the convergence?) The practical implementation actually implies using the path-space rejection sampling methods in the Read Paper of Beskos et al. (2006). (An extreme case of the algorithm is actually an (exact) ABC version where the simulations x¹,x²,… from all components have to be identical and equal to y. The opposite extreme is the consensus Monte Carlo Algorithm, which explains why this algorithm is not an efficient solution.) An alternative is based on an Ornstein-Uhlenbeck bridge. While the paper remains at a theoretical level with toy examples, I heard from the same sources that applications to more realistic problems and implementation on parallel processors is under way.

## waiting for the red lights to change

Posted in pictures, Running, Travel with tags , , , , , on December 22, 2018 by xi'an