## a most inappropriate typo!

Posted in Statistics with tags , , , on March 29, 2020 by xi'an

## Probability and Bayesian modeling [book review]

Posted in Books, Kids, R, Statistics, University life with tags , , , , , , , , , , , , , , , , , on March 26, 2020 by xi'an

Probability and Bayesian modeling is a textbook by Jim Albert [whose reply is included at the end of this entry] and Jingchen Hu that CRC Press sent me for review in CHANCE. (The book is also freely available in bookdown format.) The level of the textbook is definitely most introductory as it dedicates its first half on probability concepts (with no measure theory involved), meaning mostly focusing on counting and finite sample space models. The second half moves to Bayesian inference(s) with a strong reliance on JAGS for the processing of more realistic models. And R vignettes for the simplest cases (where I discovered R commands I ignored, like dplyr::mutate()!).

As a preliminary warning about my biases, I am always reserved at mixing introductions to probability theory and to (Bayesian) statistics in the same book, as I feel they should be separated to avoid confusion. As for instance between histograms and densities, or between (theoretical) expectation and (empirical) mean. I therefore fail to relate to the pace and tone adopted in the book which, in my opinion, seems to dally on overly simple examples [far too often concerned with food or baseball] while skipping over the concepts and background theory. For instance, introducing the concept of subjective probability as early as page 6 is laudable but I doubt it will engage fresh readers when describing it as a measurement of one’s “belief about the truth of an event”, then stressing that “make any kind of measurement, one needs a tool like a scale or ruler”. Overall, I have no particularly focused criticisms on the probability part except for the discrete vs continuous imbalance. (With the Poisson distribution not covered in the Discrete Distributions chapter. And the “bell curve” making a weird and unrigorous appearance there.) Galton’s board (no mention found of quincunx) could have been better exploited towards the physical definition of a prior, following Steve Stiegler’s analysis, by adding a second level. Or turned into an R coding exercise. In the continuous distributions chapter, I would have seen the cdf coming first to the pdf, rather than the opposite. And disliked the notion that a Normal distribution was supported by an histogram of (marathon) running times, i.e. values lower bounded by 122 (at the moment). Or later (in Chapter 8) for Roger Federer’s serving times. Incidentally, a fun typo on p.191, at least fun for LaTeX users, as

$f_{Y\ mid X}$

with an extra space between \’ and mid’! (I also noticed several occurrences of the unvoidable “the the” typo in the last chapters.) The simulation from a bivariate Normal distribution hidden behind a customised R function sim_binom() when it could have been easily described as a two-stage hierarchy. And no comment on the fact that a sample from Y-1.5X could be directly derived from the joint sample. (Too unconscious a statistician?)

When moving to Bayesian inference, a large section is spent on very simple models like estimating a proportion or a mean, covering both discrete and continuous priors. And strongly focusing on conjugate priors despite giving warnings that they do not necessarily reflect prior information or prior belief. With some debatable recommendation for “large” prior variances as weakly informative or (worse) for Exp(1) as a reference prior for sample precision in the linear model (p.415). But also covering Bayesian model checking either via prior predictive (hence Bayes factors) or posterior predictive (with no mention of using the data twice). A very marginalia in introducing a sufficient statistic for the Normal model. In the Normal model checking section, an estimate of the posterior density of the mean is used without (apparent) explanation.

“It is interesting to note the strong negative correlation in these parameters. If one assigned informative independent priors on and , these prior beliefs would be counter to the correlation between the two parameters observed in the data.”

For the same reasons of having to cut on mathematical validation and rigour, Chapter 9 on MCMC is not explaining why MCMC algorithms are converging outside of the finite state space case. The proposal in the algorithmic representation is chosen as a Uniform one, since larger dimension problems are handled by either Gibbs or JAGS. The recommendations about running MCMC do not include how many iterations one “should” run (or other common queries on Stack eXchange), albeit they do include the sensible running multiple chains and comparing simulated predictive samples with the actual data as a  model check. However, the MCMC chapter very quickly and inevitably turns into commented JAGS code. Which I presume would require more from the students than just reading the available code. Like JAGS manual. Chapter 10 is mostly a series of examples of Bayesian hierarchical modeling, with illustrations of the shrinkage effect like the one on the book cover. Chapter 11 covers simple linear regression with some mentions of weakly informative priors,  although in a BUGS spirit of using large [enough?!] variances: “If one has little information about the location of a regression parameter, then the choice of the prior guess is not that important and one chooses a large value for the prior standard deviation . So the regression intercept and slope are each assigned a Normal prior with a mean of 0 and standard deviation equal to the large value of 100.” (p.415). Regardless of the scale of y? Standardisation is covered later in the chapter (with the use of the R function scale()) as part of constructing more informative priors, although this sounds more like data-dependent priors to me in the sense that the scale and location are summarily estimated by empirical means from the data. The above quote also strikes me as potentially confusing to the students, as it does not spell at all how to design a joint distribution on the linear regression coefficients that translate the concentration of these coefficients along y̅=β⁰+β¹x̄. Chapter 12 expands the setting to multiple regression and generalised linear models, mostly consisting of examples. It however suggests using cross-validation for model checking and then advocates DIC (deviance information criterion) as “to approximate a model’s out-of-sample predictive performance” (p.463). If only because it is covered in JAGS, the definition of the criterion being relegated to the last page of the book. Chapter 13 concludes with two case studies, the (often used) Federalist Papers analysis and a baseball career hierarchical model. Which may sound far-reaching considering the modest prerequisites the book started with.

In conclusion of this rambling [lazy Sunday] review, this is not a textbook I would have the opportunity to use in Paris-Dauphine but I can easily conceive its adoption for students with limited maths exposure. As such it offers a decent entry to the use of Bayesian modelling, supported by a specific software (JAGS), and rightly stresses the call to model checking and comparison with pseudo-observations. Provided the course is reinforced with a fair amount of computer labs and projects, the book can indeed achieve to properly introduce students to Bayesian thinking. Hopefully leading them to seek more advanced courses on the topic.

Update: Jim Albert sent me the following precisions after this review got on-line:

[Disclaimer about potential self-plagiarism: this post or an edited version will eventually appear in my Books Review section in CHANCE. As appropriate for a book about Chance!]

## the ninth house

Posted in Books, Kids, University life with tags , , , , , , , , , , , , on March 6, 2020 by xi'an

“Monsters often operate metaphorically in fantasy. We can banish those literal monsters, but to banish the figurative monster at the same time does a tremendous disservice to readers, because trauma doesn’t finish with the last page of a book,. And for those of us who live with any kind of trauma in our past, the idea of purging it in some kind of magical way is offensive.” L. Bardugo, Bustle, Oct 9, 2019

As I had rather enjoyed the style of her YA Grisha series (despite a superficial scenario and equally superficial Russification of the fantasy universe there), I followed another Amazon link to Leigh Bardugo’s first “adult” novel. (Which denomination means not purposedly “young adult”!) The Ninth House. After a highly laudatory New York Times book review.

The story is rather unsurprising at one level, namely a college town (Yale, New Haven), “secret” societies (nine of them), some happy (?) few having access to magical powers, a parallel world, ghosts and demons, a freshwoman coming from a highly traumatic past and an unprivileged background, brushing with much more privileged classmates and catching up amazingly well in English literature and languages (but staying away from STEM, why is that?!), not so much an anti-hero as the author would us like to believe but who single-handedly solves a murder (or a few) and exposes some of the murderers for her own sense of justice. With a pending sequel to seek a missing paladin and mentor. With an elaborate enough style and enough twists and surprises in the plot to keep the reader hooked, especially readers with a past or a present in said college town. Or another Ivy League town.

However, there is more depth to the book than a mere exploitation of successful tropes, in that the main character is building meaning all along the book, with her supernatural abilities more curse than blessing and a massive past trauma that cannot heal and threatens to define her. Which makes the above statement from the author quite powerful. I thus found the book equally powerful, despite not being a big fan of ghost and horror stories, to the point of looking for the next installment, whenever ready.

## Glasgow [The papers of Tony Veitch]

Posted in Books, Kids, Mountains, pictures, Running, Travel with tags , , , , , , , , , , , , , on March 3, 2020 by xi'an

[I read the second volume of McIlvanney’s Laidlaw Trilogy, The papers of Tony Veitch, with the same glee as the first one. And with some nostalgia at the yearly trips to Glasgow I made over the years, albeit a decade after the book was published. Some passages were too good to be missed!]“Standing so high, Laidlaw felt the bleakness of summer on his face and understood a small truth. Even the climate here offered no favours. Standing at a bus stop, you talked out the side of your mouth, in case your lips got chapped. Maybe that was why the West of Scotland was where people put the head on one another—it was too cold to take your hands out your pockets.”

“A small and great city, his mind answered. A city with its face against the wind. That made it grimace. But did it have to be so hard? Sometimes it felt so hard. Well, that was some wind and it had never stopped blowing. Even when this place was the second city of the British Empire, affluence had never softened it because the wealth of the few had become the poverty of the many. The many had survived, however harshly, and made the spirit of the place theirs. Having survived affluence, they could survive anything. Now that the money was tight, they hardly noticed the difference. If you had it, all you did was spend it. The money had always been tight. Tell us something we don’t know. That was Glasgow. It was a place so kind it would batter cruelty into the ground. And what circumstances kept giving it was cruelty. No wonder he loved it. It danced among its own debris. When Glasgow gave up, the world could call it a day.”

“Laidlaw had a happy image of the first man out after the nuclear holocaust being a Glaswegian. He would straighten up and look around. He would dust himself down with that flicking gesture of the hands and, once he had got the strontium off the good suit, he would look up. The palms would be open.   ‘Hey,’ he would say. ‘Gonny gi’es a wee brek here? What was that about? Ye fell oot wi’ us or what? That was a liberty. Just you behave.’     Then he would walk off with that Glaswegian walk, in which the shoulders don’t move separately but the whole torso is carried as one, as stiff as a shield. And he would be muttering to himself, ‘Must be a coupla bottles of something still intact.’”
“They were sitting in the Glasgow University Club bar (…) Laidlaw was staring at his lime-juice and soda. Harkness was taking his lager like anaesthetic. Around them the heavy buildings and empty quadrangles seemed to shut out the city, giving them the feeling of being at the entrance to a shaft sunk into the past. Certainly, the only other two people in the room were having less a conversation than a seance, though they only seemed to summon the dead in order to rekill them.
The talk of the two university men reminded Laidlaw of why he had left university at the end of his first year, having passed his exams. He found that the forty-year-old man agreed with the nineteen-year-old boy. He suspected that a lot of academics lived inside their own heads so much they began to think it was Mount Sinai. He disliked the way they seemed to him to use literature as an insulation against life rather than an intensification of it.
He liked books but they were to him a kind of psychic food that should convert to energy for living. With academics the nature of their discipline seemed to preclude that. To take it that seriously would have annihilated the limits of aesthetics. Listening to their exchange of attitudes in what amounted to a private code, he didn’t regret the youthful impulse which had pushed him out into the streets and now brought him back here, by a circuitous and painful route, as an alien visitor. He didn’t want to be included in that clique of mutually supportive opinions that so often passes for culture.
He remembered what had finally crystallised his rejection of university. It had been having to read and listen to the vague nonsense of academics commenting on the vague nonsense of much of what D. H. Lawrence wrote. Coming himself from a background not dissimilar to Lawrence’s, he thought he saw fairly clearly how Lawrence had put out his eyes with visions rather than grapple with reality that was staring him in the face. You needn’t blame him for hiding but you needn’t spend volumes trying to justify it either; unless, of course, it helped to make your own hiding easier to take.
‘A lot of what passes for intellectuality’s just polysyllabic prejudice,’ Laidlaw thought aloud.”

## a little hatred [book review]

Posted in Books, pictures with tags , , , , , , , , on February 2, 2020 by xi'an

While the last books of Joe Abercrombie [I read] were not as exhilarating as the earliest ones, this first volume of a new trilogy brings back memories of the excitement of reading a radically new form of fantasy. Of realistic fantasy if both terms can be twinned together!

“Why folk insisted on singing about great warriors all the time, Rikke couldn’t have said. Why not sing about really good fishermen, or bakers, or roofers, or some other folk who actually left the world a better place, rather than heaping up corpses and setting fire to things?”

A little hatred (an obvious understatement!) takes place one to two generations later than the First Law trilogy. Meaning that the anti-heroes from the previous books have by now either died (a fairly common occurrence in Abercrombie’s universe) or aged a lot (more uncommon, except for magii—whose role is rather unclear in this story) and lost in influence for most of them. The new central characters are thus children or grand-children of these ancient characters as the clannish and feudal power structures of this universe do not allow for much social upheaval, except when workers unite and turn Luddites! The society has indeed evolved towards a sort of industrial revolution with landowners expelling farmers and turning them (as well as former soldiers) into cheap labour for emerging factories, just as in the historical England of the 19th Century… The rebellion of the workers in one of the factory towns is the main event of A little hatred and Abercrombie’s description of the event is fantastic (and ghastly). Much more than the millionth battle between the North and the Union, which ends up in a macho duel. And shows the clear superiority of female characters in that story.  I thus hope the sequel will keep up with this renewed creativity of the author!

## 夢幻花 [Dream flower]

Posted in Statistics with tags , , , , , , , , , , , on January 18, 2020 by xi'an

Another Japanese mystery novel by Higashino Keigo, which I read in French under the title La fleur de l´illusion [on a sunny Sunday afternoon, under my fig tree] and enjoyed both for its original, convoluted (and mostly convincing) plot and for the well-rendered interaction between the young protagonists. And also for having a few connections with my recent trip, from one protagonist studying nuclear physics at the University of Osaka to a visit to the back country of Katsuura. (The author himself graduated from Osaka Prefecture University with a Bachelor of Engineering degree.) Spoiler warning: the only annoying part of the plot was the resolution of the mystery via a secret society run by a few families of civil servants, which as always sounds to me like a rather cheap way out. But not enough to ruin the entire novel.

## the secret Commonwealth [book review]

Posted in Books, Kids, Travel with tags , , , , , , , , , , on January 12, 2020 by xi'an

Now that I have read The secret Commonwealth over the X break, I cannot but wait eagerly for the third volume! The book is indeed quite good, much in the spirit of the first ones in His dark materials than of the previous La belle sauvage. When La belle sauvage was at its core an oniric and symbolic tale floating on the Thames, with some events on the side, The secret Commonwealth on the opposite is much more centred on adventures and quests and a real story (or rather make it three!) and a growing threat, with side philosophical musings. Quite the opposite of the first book, in short. Even the time localisation is reverted. While La belle sauvage was taking place ten years before His dark materials, making Lyra a very young baby, this book takes place ten years later with Lyra a young adult, growing very quickly in maturity through the pages of the book. The two are so incredibly different that they could have almost be written by different authors… The secret Commonwealth is also much more cosmopolitan than its older sibling as both Lyra and Pan leave Oxford, then England to travel through Europe and Middle East towards a most dangerous destination. The central theme of the book is whether or not Reason or Rationalism should guide one’s life. Given the magical realism of the novel, where the soul of each character is expressed as a companion expressed as a particular animal, a marten called Pan (short for Pantalaimon) for Lyra, it is somewhat an easy (easier than in our own World!) plot line to dismiss rationalist thinkers pretending they do no exist. And to paint the philosophers following this route as either shallow and more interested in rethorics (than philosophy) or fake and deluded. Since Lyra reading these authors is the reason for a widening split between her and Pan, I did not find this part the best in the plot, even though it seemed inevitable. But the resulting quest and the “chance” meetings of both central characters are gripping and well-written, as well as deeply poignant. All characters build some depth, esp. compared with La belle sauvage where they were mostly caricatures. As it is very rare that the second volume in a series brings so much pleasure and improvements, I strongly recommend it (even as a start, skipping La belle sauvage !)