Archive for book review

sharp ends [book review]

Posted in Books, Kids, Travel with tags , , , , , , , on September 2, 2018 by xi'an

A chance encounter with an itinerant bookstore at the market of Tofino, Van Isle, BC, led me to buy this collection of short stories by Joe Abercrombie, called Sharp Ends. All set in the same universe as the great series of novels he wrote in the past ten years, involving second, third and fourth rate characters, with a few major ones popping in on the side. Including my favourite, Ninefinger. These short stories have appeared here and there across the years, but reading them together (for the first time) within a few days (of vacation) was utterly pleasant, with some threads running through most and some enjoyable recurrent characters. I remembered enough of the original First Law books to settle back in their universe, ten years later! And short stories are quite suited to Abercrombie’s style of stories, the dark and grim ending occurring always too quickly for the main character! Now this set me wondering as to why there was no recent book by this author, except for the disappointing young adult Half something trilogy. Which  read I did not complete. Reading his blog for the first time in many years, I learned that a new trilogy is in the making, set in the same universe (and avoiding mixing dark fantasy with western!). Looking forward this new series!!!

the ocean at the end of the lane [book review]

Posted in Books, Kids, pictures, Travel with tags , , , , , , , , , , , , , on August 24, 2018 by xi'an

While in Vancouver, waiting for a friend at the Waterfront ferry station, we entered the Simon Fraser University bookshop across the street. This was a most disconcerting experience in that the bookstore contained essentially no book! Just a tiny bookshelf with local authors and another one with a medley of genres. Including Gaiman’s The Ocean at the End of the Lane. Which I bought against my better judgement as I had tried to read American Dogs years ago and failed. (But liked very much Neverwhere, again a chance occurrence on a bookstore shelf!) As I started reading the book on the ferry to Vancouver Island, hence on the Pacific Ocean!, I first thought this was about the author’s childhood in rural Sussex, with no other friends than his books, finding some ways to relate to the story of a modest household in the early 60’s, only to be interrupted by three whales swimming along the ferry route. The cheek of them! When I picked up the short novel later in Tofino (with Tonkin Beach above), reality started to unravel (in the book!) and horror to creep in (!). Without getting into spoilers, the  other world or old country starts appearing to the narrator, a seven year old, with about everything taking another and sinister meaning. And no-one else in his household paying any attention to his warnings. What I really enjoy in the book is the sheer ambiguity of the tale, where one cannot be sure this is pure fantasy made up by a lonely seven year old who strongly dislikes a new nanny and is impacted by his parents’ relationship, or an opening into that alternate reality and its dangers that he and only he is able to enter. The book never concludes and this is a strength of the story. Which works for both adult and children readers. It also reminded me of Miyazaki’s Chihiro Spirited Away (千と千尋の神隠し), in that the supernatural beings here and there are neither evil nor good but simply utterly alien. (This fantastic² movie is considered by my daughter as the most traumatic one she ever saw as a child!) Concluding about the book, this was a very good read, somewhat on the light side although full of forking paths.

Is that a big number? [book review]

Posted in Books, Kids, pictures, Statistics with tags , , , , , , , , , on July 31, 2018 by xi'an

A book I received prior to its publication a few days ago from OXford University Press (OUP), as a book editor for CHANCE (usual provisions apply: the contents of this post will be more or less reproduced in my column in CHANCE when it appears). Copy that I found in my mailbox in Warwick last week and read over the (very hot) weekend.

The overall aim of this book by Andrew Elliott is to encourage numeracy (or fight innumeracy) by making sense of absolute quantities by putting them in perspective, teaching about log scales, visualisation, and divide-and-conquer techniques. And providing a massive list of examples and comparisons, sometimes for page after page… The book is associated with a fairly rich website, itself linked with the many blogs of the author and a myriad of other links and items of information (among which I learned of the recent and absurd launch of Elon Musk’s Tesla car in space! A première in garbage dumping…). From what I can gather from these sites, some (most?) of the material in the book seems to have emerged from the various blog entries.

“Length of River Thames (386 km) is 2 x length of the Suez Canal (193.3 km)”

Maybe I was too exhausted by heat and a very busy week in Warwick for our computational statistics week, the football  2018 World Cup having nothing to do with this, but I could not keep reading the chapters of the book in a continuous manner, suffering from massive information overdump! Being given thousands of entries kills [for me] the appeal of outing weight or sense to large and very large and humongous quantities. And the final vignette in each chapter of pairing of numbers like the one above or the one below

“Time since earliest writing (5200 y) is 25 x time since birth of Darwin (208 y)”

only evokes the remote memory of some kid journal I read from time to time as a kid with this type of entries (I cannot remember the name of the journal!). Or maybe it was a journal I would browse while waiting at the hairdresser’s (which brings back memories of endless waits, maybe because I did not like going to the hairdresser…) Some of the background about measurement and other curios carry a sense of Wikipediesque absolute in their minute details.

A last point of disappointment about the book is the poor graphical design or support. While the author insists on the importance of visualisation on grasping the scales of large quantities, and the webpage is full of such entries, there is very little backup with great graphs to be found in “Is that a big number?” Some of the pictures seem taken from an anonymous databank (where are the towers of San Geminiano?!) and there are not enough graphics. For instance, the fantastic graphics of xkcd conveying the xkcd money chart poster. Or about future. Or many many others

While the style is sometimes light and funny, an overall impression of dryness remains and in comparison I much more preferred Kaiser Fung’s Numbers rule your world and even more both Guesstimation books!

the naming of the Dead [book review]

Posted in Statistics with tags , , , , , , , , , , , , , on July 21, 2018 by xi'an

When leaving for ISBA 2018 in Edinburgh, I picked a Rebus book in my bookshelf,  book that happened to be The Naming of the Dead, which was published in 2006 and takes place in 2005, during the week of the G8 summit in Scotland and of the London Underground bombings. Quite a major week in recent British history! But also for Rebus and his colleague Siobhan Clarke, who investigate a sacrificial murder close, too close, to the location of the G8 meeting and as a result collide with superiors, secret services, protesters, politicians, and executives, including a brush with Bush ending up with his bike accident at Gleneagles, and ending up with both of them suspended from the force. But more than this close connection with true events in and around Edinburgh, the book is a masterpiece, maybe Rankin’s best, because of the depiction of the characters, who have even more depth and dimensions than in the other novels.  And for the analysis of the events of that week. Having been in Edinburgh at the time I started re-reading the book also made the description of the city much more vivid and realistic, as I could locate and sometimes remember some places. (The conclusion of some subplots may be less realistic than I would like them to be, but this is of very minor relevance.)

rather dull, if rother weird… [book review]

Posted in Books, Kids, Travel with tags , , , , , , , , , , on July 1, 2018 by xi'an

A book that I grabbed in Waterstones, Brussels, on a quick dash between two meetings. And which presumably attracted me because of the superficial [watery] similarity with the book series Rivers of London, which setting and style I like quite a lot. Or, one can always dream on, a light version of Jonathan Strange & Mr. NorrellRotherweird is the first book in a trilogy by Andrew Caldecott, taking place in a sort of time space hole in (very) rural England, the river Rother being a true river in South-East England, near Hastings, but this first book does not put me in a particularly eager mood to seek the next volumes, as I find the story, the plot, the characters, and the settings all quite disappointing. Maybe having a truly parallel universe does not help (although it worked pretty well with Jonathan Strange & Mr. Norrell!). Having a boarding school with weird teachers does not either, as they are never exhibited as particularly competent in their own field and as students are absolutely invisible in the novel, while supposed to be the brightest in the whole of England. (Which makes a comparison with Harry Potter megalogy pointless.) Having this town of Rotherweird stuck in a rather indefinite time (and banning any attempt at history) could have been a great start but characters are very shallow, despite some funny lines, and do not contribute to make the universe more conceivable, just the opposite. Without indulging in spoilers, the final resolution is very very unconvincing.

independent random sampling methods [book review]

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , on May 16, 2018 by xi'an

Last week, I had the pleasant surprise to receive a copy of this book in the mail. Book that I was not aware had been written or published (meaning that I was not involved in its review!). The three authors, Luca Martino, David Luengo, and Joaquín Míguez, of Independent Random Sampling Methods are from Madrid universities and I have read (and posted on) several of their papers on (population) Monte Carlo simulation in the recent years. Including Luca’s survey of multiple try MCMC which was helpful in writing our WIREs own survey.

The book is a pedagogical coverage of most algorithms used to simulate independent samples from a given distribution, which of course recoups some of the techniques exposed with more details by [another] Luc, namely Luc Devroye’s Non-uniform random variate generation bible, often mentioned here (and studied in uttermost details by a dedicated reading group in Warwick). It includes a whole chapter on accept-reject methods, with in particular a section on Payne-Dagpunar’s band rejection I had not seen previously. And another entire chapter on ratio-of-uniforms techniques. On which the three authors had proposed generalisations [covered by the book], years before I attempted to go the same way, having completely forgotten reading their paper at the time… Or the much earlier 1991 paper by Jon Wakefield, Alan Gelfand and Adrian Smith!

The book also covers the “vertical density representation”, due to Troutt (1991), which consists in considering the distribution of the density p(.) of the random variable X as a random variable, p(X). I remember pondering about this alternative to the cdf transform and giving up on it as the outcome has a distribution depending on p, even when the density is monotonous. Even though I am not certain from reading the section that this is particularly appealing…

Given its title, the book contains very little about MCMC. Except for a last and final chapter that covers adaptive independent Metropolis-Hastings algorithms, in connection with some of the authors’ recent work. Like multiple try Metropolis. Relating to the (unidimensional) ARMS “ancestor” of adaptive MCMC methods. (As noted in a recent blog on Holden et al., 2009 , I have trouble understanding how recycling only rejected proposed values to build a better proposal distribution is enough to guarantee convergence of an adaptive algorithm, but the book does not delve much into this convergence.)

All in all and with the bias induced by me working in the very area, I find the book quite a nice entry on the topic, which can be used in a Monte Carlo course at both undergraduate and graduate levels if one want to avoid going into Markov chains. It is certainly less likely to scare students away than the comprehensive Non-uniform random variate generation and on the opposite may induce some of them to pursue a research career in this domain.

practical Bayesian inference [book review]

Posted in Books, Kids, R, Statistics, University life with tags , , , , , , , , , on April 26, 2018 by xi'an

[Disclaimer: I received this book of Coryn Bailer-Jones for a review in the International Statistical Review and intend to submit a revised version of this post as my review. As usual, book reviews on the ‘Og are reflecting my own definitely personal and highly subjective views on the topic!]

It is always a bit of a challenge to review introductory textbooks as, on the one hand, they are rarely written at the level and with the focus one would personally choose to write them. And, on the other hand, it is all too easy to find issues with the material presented and the way it is presented… So be warned and proceed cautiously! In the current case, Practical Bayesian Inference tries to embrace too much, methinks, by starting from basic probability notions (that should not be unknown to physical scientists, I believe, and which would avoid introducing a flat measure as a uniform distribution over the real line!, p.20). All the way to running MCMC for parameter estimation, to compare models by Bayesian evidence, and to cover non-parametric regression and bootstrap resampling. For instance, priors only make their apparition on page 71. With a puzzling choice of an improper prior (?) leading to an improper posterior (??), which is certainly not the smoothest entry on the topic. “Improper posteriors are a bad thing“, indeed! And using truncation to turn them into proper distributions is not a clear improvement as the truncation point will significantly impact the inference. Discussing about the choice of priors from the beginning has some appeal, but it may also create confusion in the novice reader (although one never knows!). Even asking about “what is a good prior?” (p.73) is not necessarily the best (and my recommended) approach to a proper understanding of the Bayesian paradigm. And arguing about the unicity of the prior (p.119) clashes with my own view of the prior being primarily a reference measure rather than an ideal summary of the available information. (The book argues at some point that there is no fixed model parameter, another and connected source of disagreement.) There is a section on assigning priors (p.113), but it only covers the case of a possibly biased coin without much realism. A feature common to many Bayesian textbooks though. To return to the issue of improper priors (and posteriors), the book includes several warnings about the danger of hitting an undefined posterior (still called a distribution), without providing real guidance on checking for its definition. (A tough question, to be sure.)

“One big drawback of the Metropolis algorithm is that it uses a fixed step size, the magnitude of which can hardly be determined in advance…”(p.165)

When introducing computational techniques, quadratic (or Laplace) approximation of the likelihood is mingled with kernel estimators, which does not seem appropriate. Proposing to check convergence and calibrate MCMC via ACF graphs is helpful in low dimensions, but not in larger dimensions. And while warning about the dangers of forgetting the Jacobians in the Metropolis-Hastings acceptance probability when using a transform like η=ln θ is well-taken, the loose handling of changes of variables may be more confusing than helpful (p.167). Discussing and providing two R codes for the (standard) Metropolis algorithm may prove too much. Or not. But using a four page R code for fitting a simple linear regression with a flat prior (pp.182-186) may definitely put the reader off! Even though I deem the example a proper experiment in setting a Metropolis algorithm and appreciate the detailed description around the R code itself. (I just take exception at the paragraph on running the code with two or even one observation, as the fact that “the Bayesian solution always exists” (p.188) [under a proper prior] is not necessarily convincing…)

“In the real world we cannot falsify a hypothesis or model any more than we “truthify” it (…) All we can do is ask which of the available models explains the data best.” (p.224)

In a similar format, the discussion on testing of hypotheses starts with a lengthy presentation of classical tests and p-values, the chapter ending up with a list of issues. Most of them reasonable in my own referential. I also concur with the conclusive remarks quoted above that what matters is a comparison of (all relatively false) models. What I less agree [as predictable from earlier posts and papers] with is the (standard) notion that comparing two models with a Bayes factor follows from the no information (in order to avoid the heavily loaded non-informative) prior weights of ½ and ½. Or similarly that the evidence is uniquely calibrated. Or, again, using a truncated improper prior under one of the assumptions (with the ghost of the Jeffreys-Lindley paradox lurking nearby…).  While the Savage-Dickey approximation is mentioned, the first numerical resolution of the approximation to the Bayes factor is via simulations from the priors. Which may be very poor in the situation of vague and uninformative priors. And then the deadly harmonic mean makes an entry (p.242), along with nested sampling… There is also a list of issues about Bayesian model comparison, including (strong) dependence on the prior, dependence on irrelevant alternatives, lack of goodness of fit tests, computational costs, including calls to possibly intractable likelihood function, ABC being then mentioned as a solution (which it is not, mostly).

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