Archive for Nate Silver

coronavirus counts do not count

Posted in Books, pictures, Statistics with tags , , , , , , , , on April 8, 2020 by xi'an

Somewhat by chance I came across Nate Silver‘s tribune on FiveThirtyEight about the meaninglessness of COVID-19 case counts. As it reflects on sampling efforts and available resources rather than actual cases, furthermore sampling efforts from at least a fortnight.

“The data, at best, is highly incomplete, and often the tip of the iceberg for much larger problems. And data on tests and the number of reported cases is highly nonrandom. In many parts of the world today, health authorities are still trying to triage the situation with a limited number of tests available. Their goal in testing is often to allocate scarce medical care to the patients who most need it — rather than to create a comprehensive dataset for epidemiologists and statisticians to study.”

This article runs four different scenarios, with the same actual parameters for the epidemics, and highly different and mostly misleading perceptions based on the testing strategies. This is a highly relevant warning but I am surprised Nate Silver does not move to the rather obvious conclusion that some form of official survey or another, for instance based on capture-recapture and representative samples, testing for present and past infections, should be implemented on a very regular basis, even with a limited number of tested persons to get a much more reliable vision of the status of the epidemics. Here, the French official institute of statistics, INSEE, would be most suited to implement such a scheme.

“In short, the French presidential election is a mess”

Posted in Statistics with tags , , , , , , on April 23, 2017 by xi'an

Harry Enten (and not Nate Silver as reported by Le Monde) published yesterday a post on Five-Thirty-Eight about the unpredictability of the French elections. Which essentially states the obvious, namely that the four major candidates all stand a chance to make it to the runoff. (The post classifies Macron as a former left-wing socialist, which shows a glaring misunderstanding of the candidate or a massive divergence of what left-wing means between France and the USA.) The tribune states both that the polls could exhibit a bigger mistake than in the previous elections and that Le Pen score is unlikely to be underestimated, because voters are no longer shy to acknowledge they vote for a fascist candidate. One argument for the error in the polls is attributed to pollsters “herding” their results, i.e., shrinking the raw figures towards the global average taken over previous polls. A [rather reasonable] correction dismissed by Le Monde and French pollsters. While Enten argues that the variability of the percentages over fifty polls is too small to be plausible, assuming a Normal distribution that may not hold because French pollsters use quotas to build their polling population. In any case, this analysis, while cautious and reasonably so!, does not elaborate on the largest question mark, the elephant in the room, namely the percentage of abstentions today and their distribution among the political spectrum, which may eventually make the difference tonight. Indeed, “the bottom line is that we don’t know what’s going to happen on Sunday.” And it is definitely frightening!

2017

Posted in Books, Kids, pictures with tags , , on January 1, 2017 by xi'an

I find this xkcd entry very much in tune with my own feelings and misgivings about 2017. I like the notion that 2016 is sending us in the future without things (and people) it would have been better to keep. Like reaching out instead of building barriers, whether about staying in the EU or uniting all Americans under one’s presidency, rather than tweeting scorn, exclusion, and righteousness. Like keeping hospitals standing and operating, instead of flattening them out, in Syria, Irak, Yemen and Afghanistan. Like preserving women’s access to contraception and abortion, instead of [old men] ruling over their body and rights. No, 2017 does not look too promising.

xkcd [interview & book]

Posted in Books, Kids, Statistics with tags , , , , , , , on September 14, 2014 by xi'an

Of interest for xkcd fans: What If?: Serious Scientific Answers to Absurd Hypothetical Questions is out! Actually, it is currently the #1 bestseller on amazon! (A physics book makes it to the top of the bestseller list, a few weeks after a theoretical economics book got there. Nice! Actually, a statistics book also made it to the top: Nate Silver’s The SIgnal and the Noise….) I did not read the book, but it is made of some of the questions answered by Randall Munroe (the father of xkcd) on his what if blog. In connection with this publication, Randall Munroe is interviewed on FiveThirtyEight (Nate Silver’s website), as kindly pointed out to me by Bill Jefferys. The main message is trying to give people a feeling about numbers, a rough sense of numeracy. Which was also the purpose of the guesstimation books.

Scottish polls…

Posted in pictures, Statistics, Travel with tags , , , , , , , , on September 11, 2014 by xi'an

Hillhead Street from the Great Western Road, Glasgow westside, Apr. 20, 2012As much as I love Scotland, or because of it, I would not dream of suggesting to Scots that one side of the referendum sounds better than the other. However, I am rather annoyed at the yoyo-like reactions to the successive polls about the result, because, just like during the US elections, each poll is analysed separately rather than being pooled with the earlier ones in a reasonable meta-analysis… Where is Nate Silver when we need him?!

RSS conference in Newcastle

Posted in Books, pictures, Running, Statistics, Travel, University life with tags , , , , , , , on September 5, 2013 by xi'an

IMG_1697Although I could not stay at the RSS Annual Conference for the three days, I would have liked to do so, as there were several interesting sessions, from MCMC talks by Axel Finke, Din-Houn Lau, Anthony Lee and Michael Betancourt, to the session on Anti-fragility, the concept produced by Nassim Taleb in his latest book (reviewed before completion by Larry Wasserman). I find it rather surprising that the RSS is dedicating a whole session to this, but the usually anti-statistic stance of Taleb (esp. in The Black Swan) may explain for it (and the equally surprising debate between a “pro-Taleb” and a “pro-Silver”. I will also miss Sharon McGrayne‘s talk on the Bayesian revolution, but look forward to hear it at the Bayes-250 day in Duke next December. And I could have certainly benefited from the training session about building a package in R. It seemed, however, that one-day attendance was a choice made by many participants to the conference, judging from the ability to register for one or two days and from the (biased) sample of my friends.

Incidentally, the conference gave me the opportunity to discover Newcastle and Tynemouth, enjoying the architecture of Grey Street and running on the huge meadows almost at the city centre, among herds of cows in the morning fog. (I wish I had had more time to reach the neighbourly Hadrian wall and Durham, that I only spotted from the train to B’ham!)

Bayes’ Theorem in the 21st Century, really?!

Posted in Books, Statistics with tags , , , , , , on June 20, 2013 by xi'an

“In place of past experience, frequentism considers future behavior: an optimal estimator is one that performs best in hypothetical repetitions of the current experiment. The resulting gain in scientific objectivity has carried the day…”

Julien Cornebise sent me this Science column by Brad Efron about Bayes’ theorem. I am a tad surprised that it got published in the journal, given that it does not really contain any new item of information. However, being unfamiliar with Science, it may also be that it also publishes major scientists’ opinions or warnings, a label that can fit this column in Science. (It is quite a proper coincidence that the post appears during Bayes 250.)

Efron’s piece centres upon the use of objective Bayes approaches in Bayesian statistics, for which Laplace was “the prime violator”. He argues through examples that noninformative “Bayesian calculations cannot be uncritically accepted, and should be checked by other methods, which usually means “frequentistically”. First, having to write “frequentistically” once is already more than I can stand! Second, using the Bayesian framework to build frequentist procedures is like buying top technical outdoor gear to climb the stairs at the Sacré-Coeur on Butte Montmartre! The naïve reader is then left clueless as to why one should use a Bayesian approach in the first place. And perfectly confused about the meaning of objectivity. Esp. given the above quote! I find it rather surprising that this old saw of a  claim of frequentism to objectivity resurfaces there. There is an infinite range of frequentist procedures and, while some are more optimal than others, none is “the” optimal one (except for the most baked-out examples like say the estimation of the mean of a normal observation).

“A Bayesian FDA (there isn’t one) would be more forgiving. The Bayesian posterior probability of drug A’s superiority depends only on its final evaluation, not whether there might have been earlier decisions.”

The second criticism of Bayesianism therein is the counter-intuitive irrelevance of stopping rules. Once again, the presentation is fairly biased, because a Bayesian approach opposes scenarii rather than evaluates the likelihood of a tail event under the null and only the null. And also because, as shown by Jim Berger and co-authors, the Bayesian approach is generally much more favorable to the null than the p-value.

“Bayes’ Theorem is an algorithm for combining prior experience with current evidence. Followers of Nate Silver’s FiveThirtyEight column got to see it in spectacular form during the presidential campaign: the algorithm updated prior poll results with new data on a daily basis, nailing the actual vote in all 50 states.”

It is only fair that Nate Silver’s book and column are mentioned in Efron’s column. Because it is a highly valuable and definitely convincing illustration of Bayesian principles. What I object to is the criticism “that most cutting-edge science doesn’t enjoy FiveThirtyEight-level background information”. In my understanding, the poll model of FiveThirtyEight built up in a sequential manner a weight system over the different polling companies, hence learning from the data if in a Bayesian manner about their reliability (rather than forgetting the past). This is actually what caused Larry Wasserman to consider that Silver’s approach was actually more frequentist than Bayesian…

“Empirical Bayes is an exciting new statistical idea, well-suited to modern scientific technology, saying that experiments involving large numbers of parallel situations carry within them their own prior distribution.”

My last point of contention is about the (unsurprising) defence of the empirical Bayes approach in the Science column. Once again, the presentation is biased towards frequentism: in the FDR gene example, the empirical Bayes procedure is motivated by being the frequentist solution. The logical contradiction in “estimat[ing] the relevant prior from the data itself” is not discussed and the conclusion that Brad Efron uses “empirical Bayes methods in the parallel case [in the absence of prior information”, seemingly without being cautious and “uncritically”, does not strike me as the proper last argument in the matter! Nor does it give a 21st Century vision of what nouveau Bayesianism should be, faced with the challenges of Big Data and the like…