**J**ulien pointed out to me this terrible graph, where variations cannot be perceived and where the circles are meaningless! Two three-point curves would have been way more explicit!!!

## Archive for graphs

## ugly graph of the day

Posted in Books, Statistics with tags budget, graphs, Les Échos on February 25, 2012 by xi'an## Back from Philly

Posted in R, Statistics, Travel, University life with tags admissibility, graphs, homotopy, invariance, Larry Brown, Lasso, minimaxity, non-pa, Philadelp, Wharton Business School on December 21, 2010 by xi'an**T**he conference in honour of Larry Brown was quite exciting, with lots of old friends gathered in Philadelphia and lots of great talks either recollecting major works of Larry and coauthors or presenting fairly interesting new works. Unsurprisingly, a large chunk of the talks was about admissibility and minimaxity, with John Hartigan starting the day re-reading Larry masterpiece 1971 paper linking admissibility and recurrence of associated processes, a paper I always had trouble studying because of both its depth and its breadth! Bill Strawderman presented a new if classical minimaxity result on matrix estimation and Anirban DasGupta some large dimension consistency results where the choice of the distance (total variation versus Kullback deviance) was irrelevant. Ed George and Susie Bayarri both presented their recent work on g-priors and their generalisation, which directly relate to our recent paper on that topic. On the afternoon, Holger Dette showed some impressive mathematics based on Elfving’s representation and used in building optimal designs. I particularly appreciated the results of a joint work with Larry presented by Robert Wolpert where they classified all Markov stationary infinitely divisible time-reversible integer-valued processes. It produced a surprisingly small list of four cases, two being trivial.. The final talk of the day was about homology, which sounded a priori rebutting, but Robert Adler made it extremely entertaining, so much that I even failed to resent the powerpoint tricks! The next morning, Mark Low gave a very emotional but also quite illuminating about the first results he got during his PhD thesis at Cornell (completing the thesis when I was using Larry’s office!). Brenda McGibbon went back to the three truncated Poisson papers she wrote with Ian Johnstone (via gruesome 13 hour bus rides from Montréal to Ithaca!) and produced an illuminating explanation of the maths at work for moving from the Gaussian to the Poisson case in a most pedagogical and enjoyable fashion. Larry Wasserman explained the concepts at work behind the lasso for graphs, entertaining us with witty acronyms on the side!, and leaving out about 3/4 of his slides! (The research group involved in this project produced an R package called huge.) Joe Eaton ended up the morning with a very interesting result showing that using the right Haar measure as a prior leads to a matching prior, then showing why the consequences of the result are limited by invariance itself. Unfortunately, it was then time for me to leave and I will miss (in both meanings of the term) the other half of the talks. Especially missing Steve Fienberg’s talk for the third time in three weeks! Again, what I appreciated most during those two days (besides the fact that we were all reunited on the very day of Larry’s birthday!) was the pain most speakers went to to expose older results in a most synthetic and intuitive manner… I also got new ideas about generalising our parallel computing paper for random walk Metropolis-Hastings algorithms and for optimising across permutation transforms.

## Le Monde puzzle [48: resolution]

Posted in R, Statistics with tags graphs, Le Monde, mathematical puzzle, R on December 4, 2010 by xi'an**T**he solution to puzzle 48 given in * Le Monde* this weekend is rather direct (which makes me wonder why the solution for 6 colours is still unavailable..) Here is a quick version of the solution: Continue reading

## Le Monde puzzle [48]

Posted in R, Statistics with tags graph, graphs, Le Monde, mathematical puzzle, R, Ramsay's numbers, Ramsay's problem on December 2, 2010 by xi'an**T**his week(end), the * Le Monde* puzzle can be (re)written as follows (even though it is presented as a graph problem):

Given a square 327×327 symmetric matrix A, where each non-diagonal entry is in {1,2,3,4,5} and , does there exist a triplet (i,j,k) such that

**S**olving this problem in R is very easy. Or appears to be. We can indeed create a random matrix A and check whether or not any of the five triple indicator matrices

has a non-zero diagonal entry. Indeed, since satisfies

there is a non-zero entry iff there exists a triplet (u,v,w) such that the product is different from zero. Here is the R code:

chec=1 for (mc in 1:10^3){ #random filled matrix A=matrix(sample(1:5,(357)^2,rep=TRUE),357) A=A*upper.tri(A)+t(A*upper.tri(A)) #checking for links agr=0 for (t in 1:5){ B=(A==t) agr=max(agr,max(diag(B%*%B%*%B)>0)) if (agr==1){ break()} } chec=min(chec,agr) if (chec==0){ break()} }

**I** did run the above code and did not find any case where no triplet was sharing the same number. Neither did I for 326, 325,… But Robin Ryder told me that this is a well-known problem in graph theory that goes under the name of Ramsey’s problem and that 327 is an upper bound on the number of nodes for the existence of the triplet with 5 colours/numbers. So this is another illustration of a case when crude simulation cannot exhibit limiting cases in order to void a general property, because of the number of possible cases. To improve the chances of uncovering the boudary value, we would need a simulation that dis-favours triplets with the same number. I am also curious to see * Le Monde* solution tomorrow, since finding Ramsey’s numbers seems to be a hard problem, no solution being provided for 6 colours/numbers.

**I**ncidentally, I wonder if there is a faster way to produce a random symmetric matrix than the cumbersome

A=matrix(sample(1:5,(357)^2,rep=TRUE,357) A=A*upper.tri(A)+t(A*upper.tri(A))

Using the alternative saving on the lower triangular part

A=matrix(sample(1:5,(357)^2,rep=TRUE,357) A[upper.tri(A)]=sample(1:5,357*178,rep=TRUE) A=A*upper.tri(A)+t(A*upper.tri(A))

certainly takes longer…

## Random graphs with fixed numbers of neighbours

Posted in Books, R, Statistics with tags edges, graphs, hcl, Le Monde, nodes, R, R bug, R-graphics, sample, simulation on November 25, 2010 by xi'an**I**n connection with Le Monde puzzle #46, I eventually managed to write an R program that generates graphs with a given number *n* of nodes and a given number *k* of edges leaving each of those nodes. (My early attempt was simply too myopic to achieve any level of success when *n* was larger than 10!) Here is the core of the R code:

## Terrible graph of the weekend

Posted in Books, Statistics with tags graphs, junkchart, Le Monde, Statistics, Tufte, USA Today on May 2, 2010 by xi'an**E**very week, the weekend edition of * Le Monde* contains a tribune around some statistics and almost irremediably the illustrations are terrible. Witness the one above where the move from 940 millions to more than a billion is completely out of proportions, both for the disk areas and the number of people! Same thing for the split pie chart below:

**W**hat’s wrong with a regular pie-chart?! And the increase in disabled planes below is not much better, moving from 5 to 8 plane silhouettes… The illustrators should read Tufte’s books instead of ** USA Today**…!

**Ps-**I seem to be always picking at * Le Monde*, but this is only because I have a subscribtion to its weekend edition!