Archive for University of Glasgow

Poisson-Belgium 0-0

Posted in Statistics with tags , , , , , , , , , , , , , , , , , , , on December 5, 2022 by xi'an

“Statistical match predictions are more accurate than many people realize (…) For the upcoming Qatar World Cup, Penn’s model suggests that Belgium (…) has the highest chances of raising the famous trophy, followed by Brazil”

Even Nature had to get entries on the current football World cup, with a paper on data-analytics reaching football coaches and teams. This is not exactly prime news, as I remember visiting the Department of Statistics of the University of Glasgow in the mid 1990’s and chatting with a very friendly doctoral student who was consulting for the Glasgow Rangers (or Celtics?!) on the side at the time. And went back to Ireland to continue with a local team (Galway?!).

The paper reports on different modellings, including one double-Poisson model by (PhD) Matthew Penn from Oxford and (maths undergraduate) Joanna Marks from Warwick, which presumably resemble the double-Poisson version set by Leonardo Egidi et al. and posted on Andrews’ blog a few days ago. Following an earlier model by my friends Karlis & Ntzoufras in 2003. While predictive models can obviously fail, this attempt is missing Belgium, Germany, Switzerland, Mexico, Uruguay, and Denmark early elimination from the cup. One possible reason imho is that national teams do not play that often when players are employed by different clubs in many counties, hence are hard to assess, but I cannot claim any expertise or interest in the game.

Finite mixture models do not reliably learn the number of components

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , on October 15, 2022 by xi'an

When preparing my talk for Padova, I found that Diana Cai, Trevor Campbell, and Tamara Broderick wrote this ICML / PLMR paper last year on the impossible estimation of the number of components in a mixture.

“A natural check on a Bayesian mixture analysis is to establish that the Bayesian posterior on the number of components increasingly concentrates near the truth as the number of data points becomes arbitrarily large.” Cai, Campbell & Broderick (2021)

Which seems to contradict [my formerly-Glaswegian friend] Agostino Nobile  who showed in his thesis that the posterior on the number of components does concentrate at the true number of components, provided the prior contains that number in its support. As well as numerous papers on the consistency of the Bayes factor, including the one against an infinite mixture alternative, as we discussed in our recent paper with Adrien and Judith. And reminded me of the rebuke I got in 2001 from the late David McKay when mentioning that I did not believe in estimating the number of components, both because of the impact of the prior modelling and of the tendency of the data to push for more clusters as the sample size increased. (This was a most lively workshop Mike Titterington and I organised at ICMS in Edinburgh, where Radford Neal also delivered an impromptu talk to argue against using the Galaxy dataset as a benchmark!)

“In principle, the Bayes factor for the MFM versus the DPM could be used as an empirical criterion for choosing between the two models, and in fact, it is quite easy to compute an approximation to the Bayes factor using importance sampling” Miller & Harrison (2018)

This is however a point made in Miller & Harrison (2018) that the estimation of k logically goes south if the data is not from the assumed mixture model. In this paper, Cai et al. demonstrate that the posterior diverges, even when it depends on the sample size. Or even the sample as in empirical Bayes solutions.

The Quaker [book review]

Posted in Books, Travel with tags , , , , , , , , , , , , on February 6, 2021 by xi'an

I ordered The Quaker, a book by Liam McIlvanney mostly because Liam is the son of WIlliam McIlvanney, whose Glasgow’s Laidlaw trilogy I found stunning. I was intrigued by the attempt at following in his father’s Tartan Noir steps. To make the link stronger this book won the 2018 (William) McIlvanney Prize for crime book! While there are many similarities between the stories, if only because they both take place in Glasgow in the 1960’s, where slums were gradually demolished to become high rises (themselves demolished much later in one of Ian Rankin’s stories, if in Edinburgh), where the police was partly corrupted by local gangsters, and where (im- and e-) migration was spinning the demographics of the city, the styles are different and The Quaker does not read as a clever pastiche. It is definitely a unique and brilliant book, from the vivid depiction of the Glasgow of these times (possibly helped by the fact that many locations were familiar to me from my several visits at the University of Glasgow), to the pretty convincing plot, to the psychological depths of many (male) characters. The women in the story are indeed mostly victims of the serial killer or witnesses, possibly towards reflecting the state of gender inequality in the 1960’s (as far as I remember there were more women at the fore in WIlliam’s books), with the inclusion of a victim of the Magdalene asylums. The outlying nature of the main detective is another feature common to father and son: while McCormack does not carry philosophy books to work, he remains apart from the other detectives, including a secret that threatens both the case and his career.

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.”

Charles Rennie Mackintosh’s building destroyed all over again

Posted in Statistics with tags , , , , , , on June 16, 2018 by xi'an

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