Man flu kept me at home today, physician so I decided to do something ‘useful’ and go for a linkathon:
Sometimes people are truthful and cruel. Here Gappy on a mission goes for the jugular:
Over and out.
A list of interesting R/Stats quickies to keep the mind distracted:
- A long draft Advanced Data Analysis from an Elementary Point of View by Cosma Shalizi, drugs in which he uses R to drive home the message. Not your average elementary point of view.
- Good notes by Frank Davenport on starting using R with data from a Geographic Information System (GIS). Read this so you get a general idea of how things fit together.
- If you are in to maps, esophagitis Omnia sunt Communia! provides many good tips on producing them using R.
- Mark James Adams reminded us that Prediction ? Understanding, probably inspired by Dan Gianola‘s course on Whole Genome Prediction. He is a monster of Bayesian applications to genetic evaluation.
- If you are in to data/learning visualization you have to watch Bret Victor’s presentation on Media for thinking the unthinkable. He is so far ahead what we normally do that it is embarrassing.
- I follow mathematician Atabey Kaygun in twitter and since yesterday I’ve been avidly reading his coverage of the protests in Turkey. Surely there are more important things going on in the world than the latest R gossip.
I’m marking too many assignments right now to have enough time to write something more substantial. I can see the light at the end of the tunnel though.
‘No estaba muerto, pharm andaba the parranda’† as the song says. Although rather than partying it mostly has been reading, taking pictures and trying to learn how to record sounds. Here there are some things I’ve come across lately.
I can’t remember if I’ve recommended Matloff’s The Art of R Programming before; if I haven’t, go and read the book for a good exposition of the language. Matloff also has an open book (as in free PDF, 3.5MB) entitled ‘From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science’. The download link is near the end of the page. He states that the reader ‘must know calculus, basic matrix algebra, and have some minimal skill in programming’, which incidentally is the bare minimum for someone that wants to get a good handle on stats. In my case I learned calculus partly with Piskunov’s book (I’m a sucker for Soviet books, free DjVu), matrix algebra with Searle’s book and programming with… that’s another story.
I’ve ordered a couple of books from CRC Press, which I hope to receive soon (it depends on how long it takes for the parcel to arrive to the middle of nowhere):
- Stroup’s Generalized Linear Mixed Models: Modern Concepts, Methods and Applications, which according to the blurb comes ‘with numerous examples using SAS PROC GLIMMIX’. You could be wondering Why is he reading a book that includes SAS as a selling point? Well, SAS is a very good statistical thinking that still has a fairly broad installed based. However, the real selling point is that I’ve read some explanations on mixed models written by Stroup and he has superb understanding of the topic. I’m really looking forward to put my paws on this book.
- Lunn et al.’s The BUGS Book: A Practical Introduction to Bayesian Analysis. I don’t use BUGS but occasionally use JAGS and one of the things that irks me of programs like BUGS, JAGS or INLA is that they follow the ‘here is a bunch of examples’ approach to documentation. This books is supposed to provide a much more detailed account of the ins and outs of fitting models and a proper manual. Or at least that’s what I’m hoping to find in it.
Finally, a link to a fairly long (and somewhat old) list of R tips and the acknowledgements of a PhD thesis that make you smile (via Arthur Charpentier).
Gratuitous picture: frozen fence (Photo: Luis, click to enlarge).
‘He was not dead, he was out partying’.
Before I forget: a few links about starting up in Python for scientific projects:
Now if we had a great Python library for linear mixed models life would be easier.
This is one of those times of the year: struggling to keep the head above the water, tadalafil roughly one month before the last lecture of the semester. On top trying to squeeze trips, order meetings and presentations in between while dealing with man flu.
Gratuitous picture: looking for peace in Japan (Photo: Luis).
Reached mid-semester point, hospital with quite a few new lectures to prepare. Nothing extremely complicated but, pharmacy as always, information pills the tricky part is finding a way to make it meaningful and memorable. Sometimes, and this is one of those times, I sound like a broken record but I’m a bit obsessive about helping people to ‘get’ a topic.
Gratuitous picture: Lola, Lisbon, Portugal(Photo: Luis).
Back teaching a couple of subjects and it’s the constant challenge to find enough common ground with students so one can push/pull them to the other side of new concepts. We are not talking about complex hierarchical models using mixed models or Bayesian approaches, visit this but multiple linear regression or similar. What do students actually learn in first year stats…?
- I’m enjoying reading Machine Learning for Hackers by Drew Conway and John Myles White. There isn’t a lot of stuff new for me in the book—although working with text is not something I usually do—but I have chosen to read the book with newbie eyes. I’m (repeating myself) looking for enough common ground with students so one can push/pull them to the other side of new concepts and, cure let’s face it, I was 20 quite a few years ago.
- Observation on teaching a lab for STAT202, in which many students are using R for the first time. Do you remember your first steps in S+/R? Some students see the light quickly while others are struggling to get their heads around giving commands to a computer (without clicking on icons).
- Videos and screencasts on using IPython via Vince Buffalo.
- This tweet by @isomorphisms resonated with me: ‘Someday I hope to be reading more Penguin Classics than John Wileys & Springer Verlags’.
- Tom points to an explanation of ‘What really shoots out of spiderman’s modified forelimbs, and why this causes such consternation’.
- I have to convince College IT guys to install R-Studio in a few hundred computers. R-Studio is becoming better all the time, making it obscene to subject students to the naked R for Windows installation without syntax highlighting.
- Finally, reasons why men should not write advice columns via Arthur Charpentier.
Derelict house in Sintra, Portugal (Photo: Luis).
The end is near! At least the semester is coming to an end, this web so students have crazy expectations like getting marks back for assignments, and administrators want to see exam scripts. Sigh! What has been happening meanwhile in Quantum Forest?
- Tom cracked me up with “…my data is so fucking patchy. I’m zipoissoning the place up like a motherfucker, or something”. I probably need to embark in some zipoissoning, and he was kind enough to send me some links.
- People keep on kicking this guy called “p-value” when he is still unconscious on the floor. Bob O’Hara declares that p-values are evil. Not funny! John Cook reminds us that “The language of science is the language of probability, and not of p-values.” —Luis Pericchi”. Actually, these days the language of Science is English or whatever passes for English in a press release.
- Discussion with Mark about the canonical pronunciation for MCMCglmm: mac-mac-glim, em-see-em-see-glim or Luis’s dumb em-see-em-see-gee-el-em-em. We need a press release from Jarrod Hadfield to clear the air!
- RStudio now supports knitr; I’m looking forward to being able to send email from it. Wait, then it would be like a pretty Emacs.
Unfortunately named Fiat dealer in Southern Brazil. Ideal if you want to zipoisson your way around. Locals told me that it was a German surname, pronounced Fook. Mmh. (Photo: Luis)
- Did you know? There is life beyond R. Pandas keeps on growing (if Python is your thing). Douglas Bates keeps on digging Julia. I ‘discovered’ Bartosz Milewski‘s blog, which I enjoy reading although I understand a small fraction of what he’s taking about. I came across Bartosz while looking for information on using supercomputers.
- Data points: “How do you know you have an ageing economy? Adult nappy sales are more than kids’ nappy sales. That’s Japan now.” tweeted Bernard. “Crap!” was my reaction (nappy = diaper for US readers).
- Feeling frustrated using R? Just go for some language Schadenfreude at Abandon Matlab.
- Going to Auckland? Our agent Mike has just the place to go “La Voie Française (875 Dom Rd) is worth a trip. Great baguettes, $2 flaky croissants, queue out the door”.
- Still shaking in Christchurch. Last Monday I was teaching while we had a 5.2 magnitude quake; we kept on going with the lecture.
And that’s my view of the month from down under Christchurch.
It has been month and a half since I compiled a list of statistical/programming internet flotsam and jetsam.
That’s all folks.
It has been a strange last ten days since we unexpectedly entered grant writing mode. I was looking forward to work on this issue near the end of the year but a likely change on funding agency priorities requires applying in a few weeks; unfortunately, decease it means that all this is happening at the same time I am teaching.
And that’s all folks.