Archive for John Maynard Keynes

Philosophies, Puzzles and Paradoxes [book review]

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , on May 25, 2024 by xi'an

Yudi Pawitan and Youngjo Lee have written a book that recently caught my attention within the CRC Press list of new publications. Because philosophy, puzzles, and paradoxes are definitely of interest to me (as shown by numerous entries in the ‘Og!). The subtitle of said book is A Statistician’s Search for Truth.

Reviews of the book are already available, with for instance Andrew Gelman stating that he disagrees “with much of this book, but it’s an entertaining and thought-provoking introduction to some challenging questions” or Stephen Senn starting the foreword with “This is a remarkable book: wide-ranging, ambitious, challenging and profound but also intriguing, fascinating and original.” (Senn is also cited within the book for his discussion of our revisit of Harold Jeffreys’ Theory of Probability.) Nice cover as well (albeit I could not trace the origin of it, inside or outside the book.)

The book is made of three parts, one on the philosophical approaches to truth, scientific discovery, deduction, and induction, a second one on probability theories, with philosophical motivations, Bayesian inference, and likelihood-based inference, and a third section on paradoxes. Given that both authors are senior authors who have contributed to likelihood inference throughout their career, incl. the books In All Likelihood and Generalized Linear Models with Random Effects, the likelihood approach is somewhat privileged against other statistical resolutions towards the resolution of the paradoxes, with a defence of confidence distributions and a chapter on epistemic confidence that mostly stems from recent papers by the authors, like Pawitan et al.  (2023) and Lee and Lee (2023). I find the discussion therein somewhat unclear, esp. because the same notation Pr(.) is employed for different probability notions.

“Epistemic confidence is the objective measure of uncertainty that’s attached to single events, where the objectivity is based on a consensus of rational minds.” (p.197)

The philosophy part is following the (European) Enlightenment in producing more and more involved discussions on reason, knowledge and scientific discovery. This exploration is an easy read, as it does not delve particularly deeply in the arguments of Kant, Hume, or Popper. With the apparently unescapable mention of Gödel’s incompleteness theorem, including a sausage citation from Poincaré that reminded of that strip from Tintin in America:which, most probably, he would have applied to Ais! Several sections about pseudo-rational attempts to demonstrate the existence of Dog could have been skipped as well.

The part of probability already considers paradoxes which, like the subsequent ones are mostly the consequence of using natural (and hence ambiguous) languages instead of mathematical descriptions—incl. the statement of the Likelihood Principle. It also discusses Keynes’ logical (or imprecise) probabilities, briefly if appropriately given the pessimistic views of young Keynes on the assessment of the probability of an event. Savage is privileged enough to enjoy an entire chapter discussing his 1950’s axioms leading to the existence of a (subjective)  prior on “the states of the world”. This is followed by a chapter on Inverse probability (aka Bayesian statistics), where the authors consider Bayes’ 1763 Essay to have stayed mostly unnoticed till  the beginning of the 20th Century, which sounds a somewhat subjective judgement. (And as uncovered by Steve Stiegler, the original title of the Essay was indeed intended as a reply to Hume.) A further if short chapter is dedicated to the search for the prior distribution. Which thus gives the misguided impression that there should exist such a thing, rather than acknowledging that Bayesian statements are relative to the prior measure. The remainder of the discussion on invariant and reference priors is however mostly standard. Except when falling for the marginalisation paradox when stating that a product of improper priors implies independence on p.144.

The paradoxes examined in the final part are Allais’ (an alumni of Lycée Lakanal!), and Ellsberg’s, avatars of the Saint Petersburg paradox and referring to failing to adhere to rational decision-making and not in the least to statistics. Conjunction and inclusion “fallacious fallacies”, which are central to Kahneman’s Thinking fast and slow bestseller, and attributed to reasoning in terms of likelihood rather than of probability (without accounting for multiple testing on p.228). A whole if short chapter on the Monty Hall and three prisoners paradoxes, another predictable occurrence in a book on reasoning paradoxes. Again mostly a matter of poor wording, plus relying on the choice of an underlying probability model, for which the authors again follow a likelihood approach, the number of the prize door or of the freed prisoner being the parameter. Kyburg’s (very weak) lottery paradox and related forensic paradoxes, concluding with the rejection of judgements based solely on probability reasoning. Hempel’s paradox of the ravens, a priori unrelated with statistical evidence, but turned into one by squeezing in some sampling models. Finishing with the (envelope) exchange paradox, where the authors refuse to put a prior on the unknown parameter but end up with a solution equivalent to adopting a Jeffreys prior.

In conclusion, this attempt at connecting statistical inference and philosophy, probability concepts and rational decision making, paradoxes and modelling, within a single book is academically sound and overall enjoyable, if not outstanding or remarkable as it does not constitute a radical move away from existing analyses of those classical paradoxes. Furthermore, I find the paradoxes overwhelmingly distant from genuine statistical settings and involving a rather stretched notion of data. Still, methinks I will keep this book in my bookcase, rather than leaving it for the taking in the department coffee room!

As I was completing the book and getting towards writing this book review, I also noticed a two page blurb in Significance (May 2024 issue) written by the authors on their book. (which happens rather frequently with this magazine). Unsurprisingly, the contents provd mostly extracted from the preface and introduction With a nice ravens picture (in conjunction with the raven paradox).

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

Contextual Integrity for Differential Privacy #3 [23w5106]

Posted in Books, Mountains, pictures, Running, Statistics, Travel, University life, Wines with tags , , , , , , , , , , , , , , , , , , , , , , , , , , , , on August 4, 2023 by xi'an

Morning of diverse short talks. First talk by Bei Jiang (Edmonton) on locally processed privacy for quantile estimation, which relates very much to our ongoing research with Stan, who is starting his ERC funded PhD on privacy. Randomised response, in having a positive probability of replacing indicators in the empirical cdf by a random or perturbed version whose bias can be corrected. I may have overdone the similarity though in confusing users with agents. Followed by a hacking foray by Joel Reardon (Calgary) into how much information is transmitted by apps on completely unrelated phone activity. (Moral: Never send a bug report.)

The afternoon break saw us visiting the Frind Estate winery on the other side of the lake. Meaning not only wine tasting (great Syrah!), and discovering an hybrid grape called Maréchal Foch, but also entering the lab with its mass spectrometer. (But no glimpse of the winemaking process per se…)

Contextual Integrity for Differential Privacy #2 [23w5106]

Posted in Books, Mountains, pictures, Running, Statistics, Travel, University life, Wines with tags , , , , , , , , , , , , , , , , , , , , , , , on August 3, 2023 by xi'an

Morning of diverse short talks. First one on What are the chances? Explaining ε towards endusers by presenting odds and illustrating the impact of including one potential user’s data. Then one on re-placing DP within CI in terms of causality. And multi-agent models, illustrated by the Cambridge Analytics scandal. I am still not getting the point of the CI perspective which sounds to me like an impossibility theorem. A bit as if Statistics had stopped at “All models are wrong” (as Keynes did, in a way). And a talk on Uses & misuses of DP inference, with nice drawings explaining that publicly available information (eg, smoking causes cancer) may create breaches of privacy (Alice may have cancer). Last talk of the morning on framing effects as privileging data processors and overly technical? Fundamental law of information privacy? Got me wondering about the lack (?) of dynamic perspective so far, in the (simplistic?) sense that DP does not seem to account for potential breaches were a secondary dataset to become available with shared subjects and record linkage. (A bit of a go at GDPR, for the second time within a week.)

Before, I had a rather nice early morning in woods on top of Okanagan Lake, crossing many white tailed deer, hopefully no ticks!, as well as No trespassing signs. And a quick and c…ool swim in the Lake 20⁰ waters. No sign of the large wildfires raging south in Osoyoos or north in Kalmoops. We had a fantastic lunch break at the nearby Arrowleaf Cellars winery, with a stellar pinot noir, although this rather made the following working session harder to engage with (not mentioning the lingering jetlag)!

day one at ISBA 22

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , , , , , , , , , , on June 29, 2022 by xi'an

Started the day with a much appreciated swimming practice in the [alas warm⁺⁺⁺] outdoor 50m pool on the Island with no one but me in the slooow lane. And had my first ride with the biXi system, surprised at having to queue behind other bikes at red lights! More significantly, it was a great feeling to reunite at last with so many friends I had not met for more than two years!!!

My friend Adrian Raftery gave the very first plenary lecture on his work on the Bayesian approach to long-term population projections, which was recently  a work censored by some US States, then counter-censored by the Supreme Court [too busy to kill Roe v. Wade!]. Great to see the use of Bayesian methods validated by the UN Population Division [with at least one branch of the UN

Stephen Lauritzen returning to de Finetti notion of a model as something not real or true at all, back to exchangeability. Making me wonder when exchangeability is more than a convenient assumption leading to the Hewitt-Savage theorem. And sufficiency. I mean, without falling into a Keynesian fallacy, each point of the sample has unique specificities that cannot be taken into account in an exchangeable model. Nice to hear some measure theory, though!!! Plus a comment on the median never being sufficient, recouping an older (and presumably not original) point of mine. Stephen’s (or Fisher’s?) argument being that the median cannot be recursively computed!

Antonietta Mira and I had our ABC session this afternoon with Cecilia Viscardi, Sirio Legramanti, and Massimiliano Tamborino (Warwick) as speakers. Cecilia linked ABC with normalising flows, in collaboration with Dennis Prangle (whose earlier paper on this connection was presented as the first One World ABC seminar). Thus using past simulations to approximate the posterior by a neural network, possibly with a significant increase in computing time when compared with more rudimentary SMC-ABC methods in larger dimensions. Sirio considered summary-free ABC based on discrepancies like Rademacher complexity. Which more or less contains MMD, Kullback-Leibler, Wasserstein and more, although it seems to be dependent on the parameterisation of the observations. An interesting opening at the end was that this approach could apply to non iid settings. Massi presented a paper coauthored with Umberto that had just been arXived. On sequential ABC with a dependence on the summary statistic (hence guided). Further bringing copulas into the game, although this forces another choice [for the marginals] in the method.

Tamara Broderick talked about a puzzling leverage effect of some observations in economic studies where a tiny portion of individuals may modify the significance or the sign of a coefficient, for which I cannot tell whether the data or the reliance on statistical significance are to blame. Robert Kohn presented mixture-of-Gaussian copulas [not to be confused with mixture of Gaussian-copulas!] and Nancy Reid concluded my first [and somewhat exhausting!] day at ISBA with a BFF talk on the different statistical paradigms take on confidence (for which the notion of calibration seems to remain frequentist).

Side comments: First, most people in the conference are wearing masks, which is great! Also, I find it hard to read slides from the screen, which I presume is an age issue (?!) Even more aside, I had Korean lunch in a place that refused to serve me a glass of water, which I find amazing.

a stretched view on Keynes’ Treatise

Posted in Books, pictures, Statistics, University life with tags , , , , , , , on September 20, 2020 by xi'an

I came across a rather bemusing interpretation of Keynes’ Treatise on Probability, as a tribune in Le Monde of 6 September, as being a statement against the mathematical modelling of economy. Written by Annie Cot, professor of economics at Paris Sorbonne University. While the philosophical thread of the book is inclined towards a subjective perception of probability, albeit rejecting the Bayesian approach, and while the view on statistics is equally pessimistic, falling into the infinite regress of conditioning on the observation itself, outside a Bayesian framework, as I discussed in my 2011 paper, the book makes no mention whatsoever of economics or economic models. As far as I remember the book from reading it ten years ago. To conclude, as the author of this tribune, that Keynes rejected the viability of prevision based on economic models via this book sounds therefore stretching the facts to a fair extent.