## No review this summer

Posted in Books, Statistics, University life with tags , , , , , , , , on September 19, 2019 by xi'an

A recent editorial in Nature was a declaration by a biologist from UCL on her refusal to accept refereeing requests during the summer (or was it the summer break), which was motivated by a need to reconnect with her son. Which is a good enough reason (!), but reflects sadly on the increasing pressure on one’s schedule to juggle teaching, research, administration, grant hunting, society service, along with a balanced enough family life. (Although I have been rather privileged in this regard!) Given that refereeing or journal editing is neither visible nor rewarded, it comes as the first task to be postponed or abandoned, even though most of us realise it is essential to keep science working as a whole and to make our own papers published. I have actually noticed an increasing difficulty in the past decade to get (good) referees to accept new reviews, often asking for deadlines that are hurting the authors, like six months. Making them practically unavailable. As I mentioned earlier on this blog, it could be that publishing referees’ reports as discussions would help, since they would become recognised as (unreviewed!) publications, but it is unclear this is the solution. If judging from the similar difficulty in getting discussions for discussed papers. (As an aside, there are two exciting papers coming up for discussion in Series B, ‘Unbiased Markov chain Monte Carlo methods with couplings’ by  Pierre E. Jacob, John O’Leary and Yves F. Atchadé and in Bayesian Analysis, Latent nested nonparametric priors by Frederico Camerlenghi, David Dunson, Antonio Lijoi, Igor Prünster, and Abel Rodríguez). Which is surprising when considering the willingness of a part of the community to engage into forii discussions, sometimes of a considerable length as illustrated on Andrew’s blog.

Another entry in Nature mentioned the case of two University of København tenured professors in geology who were fired for either using a private email address (?!) or being away on field work during an exam and at a conference without permission from the administration. Which does not even remotely sound like a faulty behaviour to me or else I would have been fired eons ago..!

## buona sera da Roma [jatp]

Posted in Statistics with tags , , , , , , , on May 4, 2019 by xi'an

## Metropolis gets off the ground

Posted in Books, Kids, Statistics with tags , , , , , , , on April 1, 2019 by xi'an

An X validated discussion that toed-and-froed about an incomprehension of the Metropolis-Hastings algorithm. Which started with a blame of George Casella‘s and Roger Berger’s Statistical Inference (p.254), when the real issue was the inquisitor having difficulties with the notation V ~ f(v), or the notion of random variable [generation], mistaking identically distributed with identical. Even (me) crawling from one iteration to the next did not help at the beginning. Another illustration of the strong tendency on this forum to jettison fundamental prerequisites…

## the Grumble distribution and an ODE

Posted in Books, Kids, R, Statistics, University life with tags , , , , , , on December 3, 2014 by xi'an

As ‘Og’s readers may have noticed, I paid some recent visits to Cross Validated (although I find this too addictive to be sustainable on a long term basis!, and as already reported a few years ago frustrating at several levels from questions asked without any preliminary personal effort, to a lack of background material to understand hints towards the answer, to not even considering answers [once the homework due date was past?], &tc.). Anyway, some questions are nonetheless great puzzles, to with this one about the possible transformation of a random variable R with density

$p(r|\lambda) = \dfrac{2\lambda r\exp\left(\lambda\exp\left(-r^{2}\right)-r^{2}\right)}{\exp\left(\lambda\right)-1}$

into a Gumble distribution. While the better answer is that it translates into a power law,

$V=e^{e^{-R^2}}\sim q(v|\lambda)\propto v^{\lambda-1}\mathbb{I}_{(1,e)}(v)$,

I thought using the S=R² transform could work but obtained a wrong sign in the pseudo-Gumble density

$W=S-\log(\lambda)\sim \eth(w)\propto\exp\left(\exp(-w)-w\right)$

and then went into seeking another transform into a Gumbel rv T, which amounted to solve the differential equation

$\exp\left(-e^{-t}-t\right)\text{d}t=\exp\left(e^{-w}-w\right)\text{d}w$

As I could not solve analytically the ODE, I programmed a simple Runge-Kutta numerical resolution as follows:

solvR=function(prec=10^3,maxz=1){
z=seq(1,maxz,le=prec)
t=rep(1,prec) #t(1)=1
for (i in 2:prec)
t[i]=t[i-1]+(z[i]-z[i-1])*exp(-z[i-1]+
exp(-z[i-1])+t[i-1]+exp(-t[i-1]))
zold=z
z=seq(.1/maxz,1,le=prec)
t=c(t[-prec],t)
for (i in (prec-1):1)
t[i]=t[i+1]+(z[i]-z[i+1])*exp(-z[i+1]+
exp(-z[i+1])+t[i+1]+exp(-t[i+1]))
return(cbind(c(z[-prec],zold),t))
}


Which shows that [the increasing] t(w) quickly gets too large for the function to be depicted. But this is a fairly useless result in that a transform of the original variable and of its parameter into an arbitrary distribution is always possible, given that  W above has a fixed distribution… Hence the pun on Gumble in the title.

## [stack] overloaded, crossed and invalidated

Posted in Books, Kids, Statistics, University life with tags , , , , , , on November 21, 2011 by xi'an

For the few past days, I have been monitoring Cross Validated, a forum on statistics that is part of StackExchange (“a fast-growing network of 71 question and answer sites on diverse topics from software programming to cooking to photography and gaming“…) for questions of interest, but I think (hope?) I will stop there my involvement. First, I fear this type of forum is too addictive (at least for me, and I already have my share of web-related addictions, witness this very blog!). Of course, Cross Validated is an interesting site for questions related with statistics and machine learning, with a great LATEX interface that allows to type math formulas in a natural way; however I also find the exercise rather frustrating and to some extend futile, which is another reason why I do not wish pursuing the experience any further. For one thing, some of the questions found there are of the “please do my homework for me” type and I am plagued with enough emails of this sort (connected with my own exercises) to look for further hassle. They are however easy to spot and thus eliminate. For another, I suspect a majority of questions, while honest and deep enough, are often asked at the spur of the moment, i.e. without a preliminary search on a paper or online source, like Wikipedia or a textbook. E.g., a question about Bayes theorem that brought decent answers but not further than the Wikipedia entry on the topic. At one level, I would like to give in to temptation and to answer questions I feel I have a valid and informative answer. However, it does not seem like an efficient use of my time (read my books instead!) And also I am not completely convinced this fundamentally helps the persons who ask the questions in the first place. What may lie at the bottom of my unease with being involved in such forums is the sad fact that most questioners want answers without getting through the necessary steps of learning the bases and the background theory surrounding the question. While not being a teacher at heart, this approach gets against my views on learning (“Give a man a fish, &tc.”). Observations towards this view are that (a) many questioners are “one-shot” occurrences, i.e. are never seen again on the forum and (b) such questioners often fail to acknowledge answers that are not posted immediately, i.e. are not really interested in the debate surrounding the question they asked in the first place, only in someone solving their problem for them…

Anyway, this post is my very personal opinion on why I should not get involved with Q&A sites: it does not aim at criticising people asking or answering questions on Cross Validated, quite clearly, as some questions may lead to interesting research developments and as some answers are well-though, helpful, and informative. Just not my ballpark!