andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-243 knowledge-graph by maker-knowledge-mining
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Introduction: Chris Wilson points me to this visualizatio n of three physical models of the oil spill in the Gulf of Mexico. Cool (and scary) stuff. Wilson writes: One of the major advantages is that the models are 3D and show the plumes and tails beneath the surface. One of the major disadvantages is that they’re still just models.
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same-blog 1 0.99999994 243 andrew gelman stats-2010-08-30-Computer models of the oil spill
Introduction: Chris Wilson points me to this visualizatio n of three physical models of the oil spill in the Gulf of Mexico. Cool (and scary) stuff. Wilson writes: One of the major advantages is that the models are 3D and show the plumes and tails beneath the surface. One of the major disadvantages is that they’re still just models.
2 0.30690467 973 andrew gelman stats-2011-10-26-Antman again courts controversy
Introduction: Commenter Zbicyclist links to a fun article by Howard French on biologist E. O. Wilson: Wilson announced that his new book may be his last. It is not limited to the discussion of evolutionary biology, but ranges provocatively through the humanities, as well. . . . Generation after generation of students have suffered trying to “puzzle out” what great thinkers like Socrates, Plato, and Descartes had to say on the great questions of man’s nature, Wilson said, but this was of little use, because philosophy has been based on “failed models of the brain.” This reminds me of my recent remarks on the use of crude folk-psychology models as microfoundations for social sciences. The article also discusses Wilson’s recent crusade against selfish-gene-style simplifications of human and animal nature. I’m with Wilson 100% on this one. “Two brothers or eight cousins” is a cute line but it doesn’t seem to come close to describing how species or societies work, and it’s always seemed a
3 0.23160845 872 andrew gelman stats-2011-08-26-Blog on applied probability modeling
Introduction: Joseph Wilson points me to this blog on applied probability modeling. He sent me the link a couple months ago. If he’s still adding new entries, then his blog is probably already longer-lasting than most!
4 0.12603039 1006 andrew gelman stats-2011-11-12-Val’s Number Scroll: Helping kids visualize math
Introduction: This looks cool.
5 0.12264506 16 andrew gelman stats-2010-05-04-Burgess on Kipling
Introduction: This is my last entry derived from Anthony Burgess’s book reviews , and it’ll be short. His review of Angus Wilson’s “The Strange Ride of Rudyard Kipling: His Life and Works” is a wonderfully balanced little thing. Nothing incredibly deep–like most items in the collection, the review is only two pages long–but I give it credit for being a rare piece of Kipling criticism I’ve seen that (a) seriously engages with the politics, without (b) congratulating itself on bravely going against the fashions of the politically incorrect chattering classes by celebrating Kipling’s magnificent achievement blah blah blah. Instead, Burgess shows respect for Kipling’s work and puts it in historical, biographical, and literary context. Burgess concludes that Wilson’s book “reminds us, in John Gross’s words, that Kipling ‘remains a haunting, unsettling presence, with whom we still have to come to terms.’ Still.” Well put, and generous of Burgess to end his review with another’s quote. Other cri
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same-blog 1 0.95269626 243 andrew gelman stats-2010-08-30-Computer models of the oil spill
Introduction: Chris Wilson points me to this visualizatio n of three physical models of the oil spill in the Gulf of Mexico. Cool (and scary) stuff. Wilson writes: One of the major advantages is that the models are 3D and show the plumes and tails beneath the surface. One of the major disadvantages is that they’re still just models.
2 0.68365747 501 andrew gelman stats-2011-01-04-A new R package for fititng multilevel models
Introduction: Joscha Legewie points to this article by Lars Ronnegard, Xia Shen, and Moudud Alam, “hglm: A Package for Fitting Hierarchical Generalized Linear Models,” which just appeared in the R journal. This new package has the advantage, compared to lmer(), of allowing non-normal distributions for the varying coefficients. On the downside, they seem to have reverted to the ugly lme-style syntax (for example, “fixed = y ~ week, random = ~ 1|ID” rather than “y ~ week + (1|D)”). The old-style syntax has difficulties handling non-nested grouping factors. They also say they can estimated models with correlated random effects, but isn’t that just the same as varying-intercept, varying-slope models, which lmer (or Stata alternatives such as gllam) can already do? There’s also a bunch of stuff on H-likelihood theory, which seems pretty pointless to me (although probably it won’t do much harm either). In any case, this package might be useful to some of you, hence this note.
3 0.68327796 973 andrew gelman stats-2011-10-26-Antman again courts controversy
Introduction: Commenter Zbicyclist links to a fun article by Howard French on biologist E. O. Wilson: Wilson announced that his new book may be his last. It is not limited to the discussion of evolutionary biology, but ranges provocatively through the humanities, as well. . . . Generation after generation of students have suffered trying to “puzzle out” what great thinkers like Socrates, Plato, and Descartes had to say on the great questions of man’s nature, Wilson said, but this was of little use, because philosophy has been based on “failed models of the brain.” This reminds me of my recent remarks on the use of crude folk-psychology models as microfoundations for social sciences. The article also discusses Wilson’s recent crusade against selfish-gene-style simplifications of human and animal nature. I’m with Wilson 100% on this one. “Two brothers or eight cousins” is a cute line but it doesn’t seem to come close to describing how species or societies work, and it’s always seemed a
Introduction: David Duvenaud writes: I’ve been following your recent discussions about how an AI could do statistics [see also here ]. I was especially excited about your suggestion for new statistical methods using “a language-like approach to recursively creating new models from a specified list of distributions and transformations, and an automatic approach to checking model fit.” Your discussion of these ideas was exciting to me and my colleagues because we recently did some work taking a step in this direction, automatically searching through a grammar over Gaussian process regression models. Roger Grosse previously did the same thing , but over matrix decomposition models using held-out predictive likelihood to check model fit. These are both examples of automatic Bayesian model-building by a search over more and more complex models, as you suggested. One nice thing is that both grammars include lots of standard models for free, and they seem to work pretty well, although the
Introduction: John Salvatier pointed me to this blog on derivative based MCMC algorithms (also sometimes called “hybrid” or “Hamiltonian” Monte Carlo) and automatic differentiation as the future of MCMC. This all makes sense to me and is consistent both with my mathematical intuition from studying Metropolis algorithms and my experience with Matt using hybrid MCMC when fitting hierarchical spline models. In particular, I agree with Salvatier’s point about the potential for computation of analytic derivatives of the log-density function. As long as we’re mostly snapping together our models using analytically-simple pieces, the same part of the program that handles the computation of log-posterior densities should also be able to compute derivatives analytically. I’ve been a big fan of automatic derivative-based MCMC methods since I started hearing about them a couple years ago (I’m thinking of the DREAM project and of Mark Girolami’s paper), and I too wonder why they haven’t been used more. I
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1 0.89576888 1505 andrew gelman stats-2012-09-20-“Joseph Anton”
Introduction: I only read the review , not the book. What puzzled me was not any lack of self-awareness but rather this bit: The title of Mr. Rushdie’s new memoir . . . comes from the alias he assumed when British police told him back in 1989 that he needed a pseudonym: the Joseph comes from Joseph Conrad, the Anton from Anton Chekhov. The protection officers issued to him by the British government soon took to calling him “Joe,” an abbreviation he says he detested. The thing that I don’t understand is why he detested the nickname. If I were in a comparable situation, I think I’d appreciate if my security detail gave me a friendly nickname. Then again, with the stress that Rushdie’s been under, I can imagine all sorts of personality transformations.
2 0.84152544 149 andrew gelman stats-2010-07-16-Demographics: what variable best predicts a financial crisis?
Introduction: A few weeks ago I wrote about the importance of demographics in political trends . Today I’d like to show you how demographics help predict financial crises. Here are a few examples of countries with major crises. The working-age population in Japan peaked in the 1995 census . The 1995 Financial Crisis in Japan The working-age USA population growth slows down to unprecedented levels in 2008 (see figure below) Financial crisis of 2007-2010 . (Also, notice previous dips in 2001, 1991 and 1981, and consider the list of recessions .) China’s working-age population, age 15 to 64, has grown continuously. The labor pool will peak in 2015 and then decline. There are more charts in Demography and Growth report by the Reserve Bank of Australia: Wikipedia surveys the causes of the financial crisis, such as “liquidity shortfall in the United States banking system caused by the overvaluation of assets”. Oh my! Slightly better than the usu
same-blog 3 0.84008527 243 andrew gelman stats-2010-08-30-Computer models of the oil spill
Introduction: Chris Wilson points me to this visualizatio n of three physical models of the oil spill in the Gulf of Mexico. Cool (and scary) stuff. Wilson writes: One of the major advantages is that the models are 3D and show the plumes and tails beneath the surface. One of the major disadvantages is that they’re still just models.
4 0.83872664 1579 andrew gelman stats-2012-11-16-Hacks, maps, and moon rocks: Recent items in the sister blog
Introduction: 1. Oh no . . . Obama is doooooomed!!!!!!!!!!! (Don’t worry, it’s just Pat Caddell and Doug Schoen talking) 2. Red-blue maps for different slices of the population 3. Picasso paintings, moon rocks, and hand-written Beatles lyrics
5 0.74928063 1945 andrew gelman stats-2013-07-18-“How big is your chance of dying in an ordinary play?”
Introduction: At first glance, that’s what I thought Tyler Cowen was asking . I assumed he was asking about the characters, not the audience, as watching a play seems like a pretty safe activity (A. Lincoln excepted). Characters in plays die all the time. I wonder what the chance is? Something between 5% and 10%, I’d guess. I’d guess your chance of dying (as a character) in a movie would be higher. On the other hand, movies have lots of extras who just show up and leave; if you count them maybe the risk isn’t so high. Perhaps the right way to do this is to weight people by screen time? P.S. The Mezzanine aside, works of art and literature tend to focus on the dramatic moments of lives, so it makes sense that death will be overrepresented.
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