Archive for Mexico

a memory called Empire [book review]

Posted in Books, Kids, pictures, Travel with tags , , , , , , , , , , , on June 6, 2020 by xi'an

A pleasant read for a few afternoon breaks (and vitamin D intake), that I chose as it was nominated for the Hugo and Nebula awards as well as a Not the Booker Prize Guardian choice. But not really worth the hype I think as the novel, A Memory Called Empire, is quite unidimensional (which is unfortunate for a space opera). In that the few characters that populate the book manage to move by themselves the political structure of the interstellar universe quite substantially. Within a few days. These characters are definitely attractive but somewhat too nice to be true and the way they bond and connect with one another is just implausible, even for a science fiction novel

“…no algorithm is innocent of its designersAn algorithm is only as perfect as the person designing it.”

The most interesting part in the story, although somewhat stretched too thin, is the conflict the central character feels between her attraction to the highly sophisticated culture of the Empire and the feeling that she will never be fully incorporated within that culture. Despite mastering the language and the societal codes well-enough to reach the upper spheres of society and impact them.

“…the real inspiration for the number-noun naming system comes from the naming practices of the Mixtec people of Oaxaca…” Arkady Martine

But, beside borrowing a lot to Japanese culture, and a wee bit to Maya or Aztec societies, the universe created by Arkady Martine is quite close to ours in its mundane aspects, including plastic spoons..! With very few truly novel technologies. But with email delivered on USB keys after travelling faster than light between star systems. The threat of an alien invasion is pending, by the end of the book, paving the way for an incoming second volume.To be read…

focused Bayesian prediction

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , on June 3, 2020 by xi'an

In this fourth session of our One World ABC Seminar, my friend and coauthor Gael Martin, gave an after-dinner talk on focused Bayesian prediction, more in the spirit of Bissiri et al. than following a traditional ABC approach.  because along with Ruben Loaiza-Maya and [my friend and coauthor] David Frazier, they consider the possibility of a (mild?) misspecification of the model. Using thus scoring rules à la Gneiting and Raftery. Gael had in fact presented an earlier version at our workshop in Oaxaca, in November 2018. As in other solutions of that kind, difficulty in weighting the score into a distribution. Although asymptotic irrelevance, direct impact on the current predictions, at least for the early dates in the time series… Further calibration of the set of interest A. Or the focus of the prediction. As a side note the talk perfectly fits the One World likelihood-free seminar as it does not use the likelihood function!

“The very premise of this paper is that, in reality, any choice of predictive class is such that the truth is not contained therein, at which point there is no reason to presume that the expectation of any particular scoring rule will be maximized at the truth or, indeed, maximized by the same predictive distribution that maximizes a different (expected) score.”

This approach requires the proxy class to be close enough to the true data generating model. Or in the word of the authors to be plausible predictive models. And to produce the true distribution via the score as it is proper. Or the closest to the true model in the misspecified family. I thus wonder at a possible extension with a non-parametric version, the prior being thus on functionals rather than parameters, if I understand properly the meaning of Π(Pθ). (Could the score function be misspecified itself?!) Since the score is replaced with its empirical version, the implementation is  resorting to off-the-shelf MCMC. (I wonder for a few seconds if the approach could be seen as a pseudo-marginal MCMC but the estimation is always based on the same observed sample, hence does not directly fit the pseudo-marginal MCMC framework.)

[Notice: Next talk in the series is tomorrow, 11:30am GMT+1.]

a la casa matemática de Oaxaca [reminiscence]

Posted in Mountains, Running, Travel, University life with tags , , , , , , , , , , on December 2, 2018 by xi'an

As this was my very first trip to the CMO part of CMO-BIRS, as opposed to many visits to BIRS, Banff, here are my impressions about this other mathematical haven, aka resort, aka retreat… First definitely a very loooong trip from Paris (especially when sitting next to three drunk women speaking loudly the whole trip, thankfully incomprehensibly in Russian!), with few connections between Mexico City [airport] and Oaxaca,  adding [for me] a five and a half hour stay over in the airport, where I experimented for the first time a coffin-like “sleep pod” hostel and some welcome rest. But presumably an easier access compared with Calgary for mathematicians from the South and East of the USA. And obviously for those Central and from South Americas.Then, contrary to Banff, the place for the Casa Matemàtica Oaxaca is for the time being essentially a permanently booked hotel, rather than a dedicated conference centre. Facilities are thus less attuned to visiting mathematicians, like missing real desks in bedrooms or working rooms. Still a nice with a very peaceful inner yard (and too small a pool to consider swimming). Actually facilitating interactions when compared with Banff: blackboards in the patios, tables outside, general quiet atmosphere (except for the endlessly barking dogs in the neighbourhood). Of course the huge difference in the weathers between both places does matter. Paradoxically (given the size of Oaxaca City), CMO is more isolated than BIRS, where downtown is a mere five minute walks, even in the middle of winter. Except for the occasional blizzard. But Oaxaca offers a fabulous food scene worth the longer trip!As for outdoors, there is also a swimming pool (Cina). And back streets to run on, even though the presence of stray dogs in about every road making running broken and haphazard (never run by a dog!, which is my rule since a tiny but angry dog bit my ankle in Caracas!). Running splits up hill a few times every morning was great training! There is furthermore the possibility of sport climbing in nearby San Sebastian de Tutla, as I experienced with Aventours, a local guiding company. And bouldering in an even closer gym.

over Mexico [jatp]

Posted in Mountains, pictures, Travel with tags , , , , , , on November 21, 2018 by xi'an

surprises in probability [book review]

Posted in Books, Statistics, Travel with tags , , , , , , , , , on November 20, 2018 by xi'an

A very short book (128 pages, but with a very high price!) I received from CRC Press is Henk Tijms’ Surprises in Probability (Seventeen Short Stories). Henk Tijms is an emeritus professor of econometrics at the Vrije University in Amsterdam and he wrote these seventeen pieces either for the Dutch Statistical Society magazine or for a blog he ran for the NYt. (The video of A Night in Casablanca above is only connected to this blog through Chico mimicking the word surprise as soup+rice.)

The author mentions that the book can be useful for teachers and indeed this is a collection of surprising probability results, surprising in the sense that the numerical probabilities are not necessarily intuitive. Most illustrations involve betting of one sort or another,  with only basic (combinatorial) probability distributions involved. Readers should not worry about even this basic probability background since most statements are exposed without a proof. Most examples are very classical, from the prisoner’s problem, to the Monty Hall paradox, to the birthday problem, to Benford’s distribution of digits, to gambler’s ruin, gambler’s fallacy, and the St Petersbourg paradox, to the secretary’s problem and stopping rules. The most advanced notion is the one of (finite state) Markov chains. As martingales are only mentionned in connection with pseudo-probabilist schemes for winning the lottery. For which (our very own!) Jeff Rosenthal makes an appearance, thanks to his uncovering of the Ontario Lottery scam!

“In no other branch of mathematics is it so easy for experts to blunder as in probability theory.”  Martin Gardner

A few stories have entries about Bayesian statistics, with mentions made of the O.J. Simpson, Sally Clark and Lucia de Berk miscarriages of justice, although these mentions make the connection most tenuous. Simulation is also mentioned as a manner of achieving approximations to more complex probabilities. But not to the point of discussing surprises about simulation, which could have been the case with the simulation of rare events.

Ten most beautiful probability formulas (Story 10) reminded me of Ian Steward 17 formulas that changed the World. Obviously at another scale and in a much less convincing way. To wit, the Normal (or Gauss) density, Bayes’ formula, the gambler’s ruin formula, the squared-root formula (meaning standard deviation decreases as √n), Kelly’s betting formula (?), the asymptotic law of distribution of prime numbers (??), another squared-root formula for the one-dimensional random walk, the newsboy formula (?), the Pollaczek-Khintchine formula (?), and the waiting-time formula. I am not sure I would have included any of these…

All in all this is a nice if unsurprising database for illustrations and possibly exercises in elementary probability courses, although it will require some work from the instructor to link the statements to their proof. As one would expect from blog entries. But this makes for a nice reading, especially while traveling and I hope some fellow traveler will pick the book from where I left it in Mexico City airport.