Archive for book review

ghost town [book review]

Posted in Books, Kids, Travel, University life with tags , , , , , , , , , , , on November 7, 2015 by xi'an

During my week in Warwick, I bought a book called Ghost Town, by Catriona Troth, from the campus bookstore, somewhat randomly, mostly because its back-cover was mentioning Coventry in the early 1980’s, racial riots, and anti-skinhead demonstrations, as well as the University of Warwick. And Ska, this musical style from the 1980’s, inspired from an earlier Jamaican rhythm, which emerged in Coventry with a groups called The Specials. (And the more mainstream Madness from Camden Town.)  While this was some of the music I was listening to at that time, I was completely unaware it had started in Coventry! And Ghost Town is a popular song from The Specials.  Which thus inspired the title of the book..

Enough with preliminaries!, the book is quite a good read, although more for the very realistic rendering of the atmosphere of the early 1980’s than for the story itself, even though both are quite intermingled. Most of the book action takes place in an homeless shelter where students just out of the University (or simply jobless) run the shelter and its flow of unemployed workers moving or drifting from the closed factories of the North towards London… This is Margaret Thatcher’s era, no doubt about this!, and the massive upheaval of industrial Britain at that time is translated into the gloomy feeling of an impoverished Midlands city like Coventry. This is also the end of the 1970’s, with (more) politically active students, almost indiscriminatingly active against every perceived oppression, from racism, to repression, the war in Ireland (with the death of Bobby Sand in Maze prison, for which I remember marching in Caen…), but mostly calling for a more open society. Given the atmosphere at that time, and especially given this was the time I was a student, there is enough material to make the book quite enjoyable [for me] to read! Even though I find the personal stories of both main protagonists somewhat caricaturesque and rather predictable. And, maybe paradoxically, the overall tone of the (plot) relationship between those two is somewhat patronising and conservative. When considering that they both can afford to retreat to safe havens when need be. But this does not make the bigger picture any less compelling a read, as the description of the (easy) manipulation of the local skinheads towards more violent racism by unnamed political forces is scary, with a very sad ending.

One side comment [of no relevance] is that reading the book made me realise I had no idea what Coventry looks like: none of the parts of town mentioned there evokes anything to me as I have never ventured farther than the train station! Which actually stands outside the ring road, hence not within the city limits. I hope I can find time during one of my next trips to have a proper look at down-town Coventry!

two years eight months and twenty eight days [book review]

Posted in Books, Travel with tags , , , , , , , , on November 1, 2015 by xi'an

I have now read through Salman Rushdie‘s version of the tales of 1001 nights (which amount to two years, eight months, and twenty-eight nights—this would make exactly two years and nine months if the last month was a month of February!, not that it particularly matters). It is a fantastic tale, with supernatural jinns playing an obviously supernatural role, a tale which plot does not matter very much as it is the (Pandora) box for more tales and deeper philosophical reflections about religion and rationality. It is not a novel and even less a science-fiction novel as I read it in some reviews.

“It was the ungodly who had been specified as the targets but (…) this place was not at all ungodly. In point of fact it was excessively godly.”

What I liked very much, besides the literary style and the almost overwhelming culture (or cultures) of the author—of which I certainly missed a large chunk!—, in two years, eight months, and twenty-eight nights is the mille-feuille structure of the story and the associated distanciation imposed upon the reader against a natural reader’s tendency to believe or want to believe despite all inconsistencies. An induced agnosticism of sorts most appropriate to mock the irrationality of religious believers, jinns and humans alike, in a godless universe: while jinn magic abounds in the book, there is no god or at least no acting god that we can detect. But gods and religious beliefs are exploited in the war of the jinns against the hapless humans. There are just as many levels of irony therein, which further contribute to skepticism and disbelief.

“Many, including the present author, trace the beginnings of the so-called “death of the gods”, back to this period.”

The book is also very much embedded in today’s world, for all its connections with medieval philosophy and the historical character Ibn Rushdn (whose name was borrowed by Rushdie’s father to become their family name) or Averroes. The War on Terror, the Afghan and Syrian rise of religious fundamentalists, the Wall Street excesses, even the shooting down of the Malaysian airline MH17 by Ukrainian rebels, all take place in the background of the so-called war of the jinns. Which makes the conclusion of the book highly pessimistic if in tune with the overall philosophical cynicism of the author: if it really takes magical forces and super-heroes to bring rationality to the world, there is little hope for our own world…

“He passed a woman with astonishing face makeup, a zipper running down the middle of her face, `unzipped’ around her mouth to reveal bloody skinless flesh all the way down her chin.”

A last remark is that the above description of an Halloween disguise reminded me of the disguise my friend Julien Cornebise opted for a few years ago! No surprise as this is exactly the same. Which shows that Rushdie and he share some common background in popular culture.

Think Bayes: Bayesian Statistics Made Simple

Posted in Books, Kids, R, Statistics, University life with tags , , , , , , , , on October 27, 2015 by xi'an

Almost Bayes can!By some piece of luck, I came upon the book Think Bayes: Bayesian Statistics Made Simple, written by Allen B. Downey and published by Green Tea Press [which I could relate to No Starch Press, focussing on coffee!, which published Statistics Done Wrong that I reviewed a while ago] which usually publishes programming books with fun covers. The book is available on-line for free in pdf and html formats, and I went through it during a particularly exciting administrative meeting…

“Most books on Bayesian statistics use mathematical notation and present ideas in terms of mathematical concepts like calculus. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be an integral in a math book becomes a summation, and most operations on probability distributions are simple loops.”

The book is most appropriately published in this collection as most of it concentrates on Python programming, with hardly any maths formula. In some sense similar to Jim Albert’s R book. Obviously, coming from maths, and having never programmed in Python, I find the approach puzzling, But just as obviously, I am aware—both from the comments on my books and from my experience on X validated—that a large group (majority?) of newcomers to the Bayesian realm find the mathematical approach to the topic a major hindrance. Hence I am quite open to this editorial choice as it is bound to include more people to think Bayes, or to think they can think Bayes.

“…in fewer than 200 pages we have made it from the basics of probability to the research frontier. I’m very happy about that.”

The choice made of operating almost exclusively through motivating examples is rather traditional in US textbooks. See e.g. Albert’s book. While it goes against my French inclination to start from theory and concepts and end up with illustrations, I can see how it operates in a programming book. But as always I fear it makes generalisations uncertain and understanding more shaky… The examples are per force simple and far from realistic statistics issues. Hence illustrates more the use of Bayesian thinking for decision making than for data analysis. To wit, those examples are about the Monty Hall problem and other TV games, some urn, dice, and coin models, blood testing, sport predictions, subway waiting times, height variability between men and women, SAT scores, cancer causality, a Geiger counter hierarchical model inspired by Jaynes, …, the exception being the final Belly Button Biodiversity dataset in the final chapter, dealing with the (exciting) unseen species problem in an equally exciting way. This may explain why the book does not cover MCMC algorithms. And why ABC is covered through a rather artificial normal example. Which also hides some of the maths computations under the carpet.

“The underlying idea of ABC is that two datasets are alike if they yield the same summary statistics. But in some cases, like the example in this chapter, it is not obvious which summary statistics to choose.¨

In conclusion, this is a very original introduction to Bayesian analysis, which I welcome for the reasons above. Of course, it is only an introduction, which should be followed by a deeper entry into the topic, and with [more] maths. In order to handle more realistic models and datasets.

Mathematical underpinnings of Analytics (theory and applications)

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , , , on September 25, 2015 by xi'an

“Today, a week or two spent reading Jaynes’ book can be a life-changing experience.” (p.8)

I received this book by Peter Grindrod, Mathematical underpinnings of Analytics (theory and applications), from Oxford University Press, quite a while ago. (Not that long ago since the book got published in 2015.) As a book for review for CHANCE. And let it sit on my desk and in my travel bag for the same while as it was unclear to me that it was connected with Statistics and CHANCE. What is [are?!] analytics?! I did not find much of a definition of analytics when I at last opened the book, and even less mentions of statistics or machine-learning, but Wikipedia told me the following:

“Analytics is a multidimensional discipline. There is extensive use of mathematics and statistics, the use of descriptive techniques and predictive models to gain valuable knowledge from data—data analysis. The insights from data are used to recommend action or to guide decision making rooted in business context. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with the entire methodology.”

Barring the absurdity of speaking of a “multidimensional discipline” [and even worse of linking with the mathematical notion of dimension!], this tells me analytics is a mix of data analysis and decision making. Hence relying on (some) statistics. Fine.

“Perhaps in ten years, time, the mathematics of behavioural analytics will be common place: every mathematics department will be doing some of it.”(p.10)

First, and to start with some positive words (!), a book that quotes both Friedrich Nietzsche and Patti Smith cannot get everything wrong! (Of course, including a most likely apocryphal quote from the now late Yogi Berra does not partake from this category!) Second, from a general perspective, I feel the book meanders its way through chapters towards a higher level of statistical consciousness, from graphs to clustering, to hidden Markov models, without precisely mentioning statistics or statistical model, while insisting very much upon Bayesian procedures and Bayesian thinking. Overall, I can relate to most items mentioned in Peter Grindrod’s book, but mostly by first reconstructing the notions behind. While I personally appreciate the distanced and often ironic tone of the book, reflecting upon the author’s experience in retail modelling, I am thus wondering at which audience Mathematical underpinnings of Analytics aims, for a practitioner would have a hard time jumping the gap between the concepts exposed therein and one’s practice, while a theoretician would require more formal and deeper entries on the topics broached by the book. I just doubt this entry will be enough to lead maths departments to adopt behavioural analytics as part of their curriculum… Continue reading

Mýrin aka Jar City [book review]

Posted in Books, Mountains, pictures, Travel with tags , , , , , , , , , , on July 26, 2015 by xi'an

Mýrin (“The Bog”) is the third novel in the Inspector Erlendur series written by Arnaldur Indridason. It contains the major themes of the series, from the fascination for unexplained disappearances in Iceland to Elendur’s inability to deal with his family responsibilities, to domestic violence, to exhumations. The death that starts the novel takes place in the district of Norðurmýri, “the northern marsh”, not far from the iconic Hallgrimskirkja, and not far either from DeCODE, the genetic company I visited last June and which stores genetic information about close to a million Icelanders, the Íslendingabók. And which plays an important and nefarious role in the current novel. While this episode takes place mostly between Reykjavik and Keflavik, hence does not offer any foray into Icelandic landscapes, it reflects quite vividly on the cultural pressure still present in the recent years to keep rapes and sexual violence a private matter, hidden from an indifferent or worse police force. It also shows how the police misses (in 2001) the important genetic clues for being yet unaware of the immense and frightening possibilities of handling the genetic code of an entire population. (The English and French titles refer to the unauthorised private collections of body part accumulated [in jars] by doctors after autopsies, families being unaware of the fact.) As usual, solving the case is the least important part of the story, which tells about broken lifes and survivors against all odds.

Bayesian inference for partially identified models [book review]

Posted in Books, Statistics, University life with tags , , , , , , , , , on July 9, 2015 by xi'an

“The crux of the situation is that we lack theoretical insight into even quite basic questions about what is going on. More particularly, we cannot sayy anything about the limiting posterior marginal distribution of α compared to the prior marginal distribution of α.” (p.142)

Bayesian inference for partially identified models is a recent CRC Press book by Paul Gustafson that I received for a review in CHANCE with keen interest! If only because the concept of unidentifiability has always puzzled me. And that I have never fully understood what I felt was a sort of joker card that a Bayesian model was the easy solution to the problem since the prior was compensating for the components of the parameter not identified by the data. As defended by Dennis Lindley that “unidentifiability causes no real difficulties in the Bayesian approach”. However, after reading the book, I am less excited in that I do not feel it answers this type of questions about non-identifiable models and that it is exclusively centred on the [undoubtedly long-term and multifaceted] research of the author on the topic.

“Without Bayes, the feeling is that all the data can do is locate the identification region, without conveying any sense that some values in the region are more plausible than others.” (p.47)

Overall, the book is pleasant to read, with a light and witty style. The notational conventions are somewhat unconventional but well explained, to distinguish θ from θ* from θ. The format of the chapters is quite similar with a definition of the partially identified model, an exhibition of the transparent reparameterisation, the computation of the limiting posterior distribution [of the non-identified part], a demonstration [which it took me several iterations as the English exhibition rather than the French proof, pardon my French!]. Chapter titles suffer from an excess of the “further” denomination… The models themselves are mostly of one kind, namely binary observables and non-observables leading to partially observed multinomials with some non-identifiable probabilities. As in missing-at-random models (Chapter 3). In my opinion, it is only in the final chapters that the important questions are spelled-out, not always faced with a definitive answer. In essence, I did not get from the book (i) a characterisation of the non-identifiable parts of a model, of the  identifiability of unidentifiability, and of the universality of the transparent reparameterisation, (ii) a tool to assess the impact of a particular prior and possibly to set it aside, and (iii) a limitation to the amount of unidentifiability still allowing for coherent inference. Hence, when closing the book, I still remain in the dark (or at least in the grey) on how to handle partially identified models. The author convincingly argues that there is no special advantage to using a misspecified if identifiable model to a partially identified model, for this imbues false confidence (p.162), however we also need the toolbox to verify this is indeed the case.

“Given the data we can turn the Bayesian computational crank nonetheless and see what comes out.” (p.xix)

“It is this author’s contention that computation with partially identified models is a “bottleneck” issue.” (p.141)

Bayesian inference for partially identified models is particularly concerned about computational issues and rightly so. It is however unclear to me (without more time to invest investigating the topic) why the “use of general-purpose software is limited to the [original] parametrisation” (p.24) and why importance sampling would do better than MCMC on a general basis. I would definitely have liked more details on this aspect. There is a computational considerations section at the end of the book, but it remains too allusive for my taste. My naïve intuition would be that the lack of identifiability leads to flatter posterior and hence to easier MCMC moves, but Paul Gustafson reports instead bad mixing from standard MCMC schemes (like WinBUGS).

In conclusion, the book opens a new perspective on the relevance of partially identifiable models, trying to lift the stigma associated with them, and calls for further theory and methodology to deal with those. Here are the author’s final points (p.162):

  • “Identification is nuanced. Its absence does not preclude a parameter being well estimated, not its presence guarantee a parameter can be well estimated.”
  • “If we really took limitations of study designs and data quality seriously, then partially identifiable models would crop up all the time in a variety of scientific fields.”
  • “Making modeling assumptions for the sole purpose of gaining full identification can be a mug’s game (…)”
  • “If we accept partial identifiability, then consequently we need to regard sample size differently. There are profound implications of posterior variance tending to a positive limit as the sample size grows.”

These points may be challenging enough to undertake to read Bayesian inference for partially identified models in order to make one’s mind about their eventual relevance in statistical modelling.

[Disclaimer about potential self-plagiarism: this post will also be published as a book review in my CHANCE column. ]

the girl who saved the king of Sweden [book review]

Posted in Books, Kids, Travel with tags , , , , , , , , , , , on June 27, 2015 by xi'an

When visiting a bookstore in Florence last month, during our short trip to Tuscany, I came upon this book with enough of a funny cover and enough of a funny title (possibly capitalising on the similarity with “the girl who played with fire”] to make me buy it. I am glad I gave in to this impulse as the book is simply hilarious! The style and narrative relate rather strongly to the series of similarly [mostly] hilarious picaresque tales written by Paasilina and not only because both authors are from Scandinavia. There is the same absurd feeling that the book characters should not have this sort of things happening to them and still the morbid fascination to watch catastrophe after catastrophe being piled upon them. While the story is deeply embedded within the recent history of South Africa and [not so much] of Sweden for the past 30 years, including major political figures, there is no true attempt at making the story in the least realistic, which is another characteristic of the best stories of Paasilina. Here, a young girl escapes the poverty of the slums of Soweto, to eventually make her way to Sweden along with a spare nuclear bomb and a fistful of diamonds. Which alas are not eternal… Her intelligence helps her to overcome most difficulties, but even her needs from time to time to face absurd situations as another victim. All is well that ends well for most characters in the story, some of whom one would prefer to vanish in a gruesome accident. Which seemed to happen until another thread in the story saved the idiot. The satire of South Africa and of Sweden is most enjoyable if somewhat easy! Now I have to read the previous volume in the series, The Hundred-Year-Old Man Who Climbed Out of the Window and Disappeared!


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