R for dummies

Just saw this nice review of R for dummies. And thought after this afternoon class that my students in the simulation course at Paris-Dauphine could clearly benefit from reading it! They in fact had a terrible time simulating a truncated normal distribution by accept-reject. As they could not get the notion of normalising constants… (Yes, indeed, this very truncated normal distribution!) Even the validity of simulating a normal variate until the truncation is satisfied was not obvious to them and they took forever to program the corresponding code. Anyway, I will certainly order the book to check for myself (after receiving Genetics for dummies to make sure I use the right vocabulary, even though it is a bit too light in the end…)! And write a review for CHANCE if it generates enough interest in doing so…

Planet Particle Physics [blog aggregator]

I just received an email from Austria that the ‘Og is now part of a blog aggregator, Particle physics planet, along with an impressive list of particle physics blogs. It is certainly an honour to be associated with this blog, even though I fear my random ratiocinations very rarely reach the shore of the particle physics universe…. (I think this is my third “aggregation” after becoming part of R-bloggers and of mathblogging.org)

1500th, 3000th, &tc

As the ‘Og reached its 1500th post and 3000th comment at exactly the same time, a wee and only mildly interesting Sunday morning foray in what was posted so far and attracted the most attention (using the statistics provided by wordpress). The most visited posts:

Title	Views
Home page	203,727
In{s}a(ne)!!	7,422
“simply start over and build something better”	6,264
Julien on R shortcomings	2,676
Sudoku via simulated annealing	2,402
About	1,876
Of black swans and bleak prospects	1,768
Solution manual to Bayesian Core on-line	1,628
Parallel processing of independent Metropolis-Hastings algorithms	1,625
Bayesian p-values	1,595
Bayes’ Theorem	1,537
#2 blog for the statistics geek?!	1,526
Do we need an integrated Bayesian/likelihood inference?	1,501
Coincidence in lotteries	1,396
Solution manual for Introducing Monte Carlo Methods with R	1,340
Julian Besag 1945-2010	1,293
Tornado in Central Park	1,093
The Search for Certainty	1,016

Hence, three R posts (incl. one by Julien and one by Ross Ihaka), three (critical) book reviews, two solution manuals, two general Bayesian posts, two computational entries, one paper (with Pierre Jacob and Murray Smith), one obituary, and one photograph news report… Altogether in line with the main purpose of the ‘Og. The most commented posts:

Post	Comments
In{s}a(ne)!!	31
“simply start over and build something better”	30
That the likelihood principle does not hold…	23
Incoherent inference	23
Lack of confidence in ABC model choice	20
Parallel processing of independent Metropolis-Hastings algorithms	19
ABC model choice not to be trusted	17
MCMC with errors	16
Coincidence in lotteries	16
Bessel integral	14
Numerical analysis for statisticians	14

Not exactly the same as above! In particular, the posts about ABC model choice and our PNAS paper got into the list. At last, the top search terms:

Search	Views
surfers paradise	1,050
benidorm	914
introducing monte carlo methods with r	514
andrew wyeth	398
mistborn	352
abele blanc	350
nested sampling	269
particle mcmc	269
bayesian p-value	263
julian besag	257
rites of love and math	249
millenium	237
bayesian p value	222
marie curie	221
bonsai	200

(out of which I removed the dozens of variations on xian’s blog). I find it rather sad that both top entries are beach towns that are completely unrelated to my lifestyle and to my vacation places. Overall, more than a  half of those entries do not strongly relate to the contents of the ‘Og (even though I did post at length about Saunderson’s Mistborn and Larsson’s Millenium trilogies). At last, the most popular clicks are

URL	Clicks
amazon.com/gp/product/1441915753?ie=UTF8&tag=chrprobboo-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=1441915753	1,243
stat.columbia.edu/~cook/movabletype/mlm	1,039
terrytao.wordpress.com	583
amazon.com/gp/product/0387389792?ie=UTF8&tag=chrprobboo-20&linkCode=as2&camp=1789&creative=9325&creativeASIN=0387389792	575
arxiv.org/abs/1012.2184	531
radfordneal.wordpress.com/2010/08/15/two-surpising-things-about-r	529
romainfrancois.blog.free.fr	505
statisfaction.wordpress.com	404
ceremade.dauphine.fr/~xian/basudo.R	395
stackoverflow.com/questions/3706990/is-r-that-bad-that-it-should-be-rewritten-from-scratch	372
amazon.com/gp/product/0387212396?ie=UTF8&tag=chrprobboo-20&linkCode=as2&camp=1789&creative=9325&creativeASIN=0387212396	298
radfordneal.wordpress.com/2010/09/03/fourteen-patches-to-speed-up-r	298
cs.ubc.ca/~cornebis	288
statisticsforum.wordpress.com	282
arxiv.org/abs/1001.2906	279
arxiv.org/abs/1010.1595	257
amazon.com/gp/redirect.html?ie=UTF8&location=http://www.amazon.com/gp/entity/-/B001H6GSKC&tag=chrprobboo-20&linkCode=ur2&camp=1789&creative=390957	256
ceremade.dauphine.fr/~xian/BCS/solutions.pdf	253
rss.org.uk/main.asp?page=3005	243
www3.interscience.wiley.com/cgi-bin/fulltext/119424936/PDFSTART	216
stat.auckland.ac.nz/~ihaka/downloads/Compstat-2008.pdf	203

which include links to my books on Amazon, Andrew Gelman’s, Terry Tao’s, Radford Neal’s and Romain François’s blogs, the CREST stat students collective blog, and a few arXiv papers of mine’s…

quantum forest

Thanks to a link on R-bloggers, I was introduced to Luis Apiolaza’s blog, Quantum Forest, which covers data analyses and R comments he encounters in his research as a quantitative forester/geneticist. And he works at the University of Canterbury, Christchurch, where I first taught from Bayesian Core in 2006. Which may be why he chose Bayesian Core as one of the three books he is currently reading to understand Bayesian statistics better. (The other two are Jim Albert’s Bayesian computation with R, and Bill Bolstad’s Introduction to Bayesian Statistics, which is not the one I reviewed recently.) Luis has just started the book but he mentions that “the book has managed to capture my interest”, which is real nice, and being annoyed by the self-contained label we put on the back cover. Which is a reaction I also got from some students when teaching the book for a week in Australia, as they thought they could take it without a probability background. Hopefully, we’ll manage to complete our revision before next summer!

A dubious statistic

Following a link on R-bloggers, I ended up on this page (with a completely useless graph that only contained the pieces of information 5% in 1900 and 55% in 2000). The author (Ralph Keeney) reports on “A remarkable 55 percent of deaths for people age 15 to 64 can be attributed to decisions with readily available alternatives.” This sounded to me like a highly dubious finding… So I looked at the paper itself, reading that

“A personal decision is a situation where an individual can make a choice among two or more alternatives. This assumes that the individual recognizes that he or she has a choice and has control of this choice. Readily available alternatives are alternatives that the decision maker would have known about and could have chosen without investing much time or money.” Ralph Keeney

This categorisation of deaths is highly debatable, in that choice is not always that available! So I do not see how the author can assert which percentage of the individuals truly have control of the choice… (For instance, can people refuse doing dangerous jobs when they desperately need a job? or when the dangerousness is an abstract concept as, say, for a Fukushima worker? Is obesity a sheer matter of will?) Furthermore, the jump from 5% to 55% is also highly shaky: “Clearly, one should not put much credibility in this 22% for 1950 or the corresponding 5% for 1900″.  In the end, tt seems that the whole issue of the paper is about the amount of information: “in 1900 the knowledge about and ability to avoid many of the causes of death would seem to be much lower than in 2000″. So life has not been getting more dangerous or people sillier, simply information about the causes of deaths has become more widespread. I am thus surprised at the low level of academic input contained in the paper (look at the “life-saving decisions’!), which may actually explain for the echo it found on the blogosphere. (This post also appeared on the Statistics Forum.)