Archive for Hastings

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.

a bar for MCMC algorithms [jatp]

Posted in pictures, Travel, Wines with tags , , , , , , , on June 8, 2017 by xi'an

Hastings without Metropolis

Posted in Books, Kids, Travel with tags , , , , , , , on October 14, 2016 by xi'an

Today marks the 950th anniversary of the battle of Hastings, when Guillaume, Duke of Normandy and pretendent to the throne of England following the death of the childless King Edward the Confessor in January 1066, defeated Harold Godwinson, recently elected King and even more recently the victor of a battle against another pretended, Harald Hardrada of Norway. (I had always thought that Guillaume had fought the battle the day his fleet of hundreds of Viking drakkars landed, but he arrived two weeks earlier and had time to build a fort in Hastings.) One of the consequences of this victory would be significant changes in the structure and vocabulary of the English language. [One may wonder at why I am mentioning this anniversary but been “born and raised” in the heart of Guillaume’s Norman kingdom prompted some long-lasting interest in the Norman invasion.]

Biometrika, volume 100

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , , on March 5, 2013 by xi'an

I had been privileged to have a look at a preliminary version of the now-published retrospective written by Mike Titterington on the 100 first issues of Biometrika (more exactly, “from volume 28 onwards“, as the title state). Mike was the dedicated editor of Biometrika for many years and edited a nice book for the 100th anniversary of the journal. He started from the 100th most highly cited papers within the journal to build a coherent chronological coverage. From a Bayesian perspective, this retrospective starts with Maurice Kendall trying to reconcile frequentists and non-frequentists in 1949, while having a hard time with fiducial statistics. Then Dennis Lindley makes it to the top 100 in 1957 with the Lindley-Jeffreys paradox. From 1958 till 1961, Darroch is quoted several times for his (fine) formalisation of the capture-recapture experiments we were to study much later (Biometrika, 1992) with Ed George… In the 1960’s, Bayesian papers became more visible, including Don Fraser (1961) and Arthur Dempster’ Demspter-Shafer theory of evidence, as well as George Box and co-authors (1965, 1968) and Arnold Zellner (1964). Keith Hastings’ 1970 paper stands as the fifth most highly cited paper, even though it was ignored for almost two decades. The number of Bayesian papers kept increasing. including Binder’s (1978) cluster estimation, Efron and Morris’ (1972) James-Stein estimators, and Efron and Thisted’s (1978) terrific evaluation of Shakespeare’s vocabulary. From then, the number of Bayesian papers gets too large to cover in its entirety. The 1980’s saw papers by Julian Besag (1977, 1989, 1989 with Peter Clifford, which was yet another precursor MCMC) and Luke Tierney’s work (1989) on Laplace approximation. Carter and Kohn’s (1994) MCMC algorithm on state space models made it to the top 40, while Peter Green’s (1995) reversible jump algorithm came close to Hastings’ (1970) record, being the 8th most highly cited paper. Since the more recent papers do not make it to the top 100 list, Mike Titterington’s coverage gets more exhaustive as the years draw near, with an almost complete coverage for the final years. Overall, a fascinating journey through the years and the reasons why Biometrika is such a great journal and constantly so.

Reading classics (#5)

Posted in Books, Statistics, University life with tags , , , , , , , , , on December 14, 2012 by xi'an

https://i2.wp.com/biomet.oxfordjournals.org/content/99/4.cover.gif

This week, my student Dona Skanji gave a presentation of the paper of Hastings “Monte Carlo sampling methods using Markov chains and their applications“, which set the rules for running MCMC algorithms, much more so than the original paper by Metropolis et al. which presented an optimisation device. even though the latter clearly stated the Markovian principle of those algorithms and their use for integration. (This is definitely a classic, selected in the book Biometrika: One hundred years, by Mike Titterington and David Cox.) Here are her slides (the best Beamer slides so far!):

Given that I had already taught my lectures on Markov chains and on MCMC algorithms, the preliminary part of Dona’s talk was easier to compose and understanding the principles of the method was certainly more straightforward than for the other papers in the series. I think she nonetheless did a rather good job in summing up the paper, running this extra simulation for the Poisson distribution—with the interesting “mistake” of including the burnin time in the representation of the output and concluding about a poor convergence—and mentioning the Gibbs extension.I led the discussion of the seminar towards irreducibility conditions and Peskun’s ordering of Markov chains, which maybe could have been mentioned by Dona since she was aware Peskun was Hastings‘ student.