Apr 242019

Back in the mist of time, when I should have been was working on my PhD, I found a blue book on the shelf that a previous occupant of the office had left there. As I learned later, it was The Blue Book that introduced the S language, the predecessor of R. I got sidetracked (as you do) and taught myself how to produce beautiful graphs in what is now known as base R, and how to run poorly understood time series analyses (impossible in SPSS at this point).

A little later, I got hooked on Stata, and to the present day, I refuse to be Stata-shamed, as Ben Stanley put it. 95 per cent of the time, it does the job, and quickly so. Also, the documentation is simply excellent.

But every now and then, I came back to R because I needed something specific. And it was mostly fun. Having access to all these APIs (in fact, concurrently having more than one data set in memory) was exciting. Having a real, reasonably straightforward scripting /programming language at my disposal instead of Stata’s hodgepodge of three (four if you count the graph language) half-baked syntaxes was exhilarating. Having a go at the latest methods on the basis of nothing more than skimming a working paper (skipping every non-trivial equation) was… I guess a little bit like trimming your hair with a chainsaw.

But finding, installing, updating and then loading three packages, just to make recoding a little more intuitive? Seriously, R? Not so cool. In fact, finding a variable (whose name and data set must be given in full) was usually enough to reduce me to tears. Attach() somehow never does what I think it should do. And so, I would return to Stata once more, like <insert awkward metaphor>.

Then, during one of my last forays, I began playing with the tidyverse. And as the young ones are prone to say: my mind was blown. Tibbles! Pipelines! Lots of yummie helper functions! Going from long to wide format and back (in various different ways)! Grouping, summarising, and even some pythonesque list traversing. This was no longer the fascinating but slightly stroppy R I used to know.

Compared to the handful of letters and abbreviations that I use in Stata to get things done, recoding-wise, this is still quite verbose, and I have to look up just about everything. But I really like it. Like, really like it. And so doing more stuff in R is firmly on the endless List Of Things I Want To Look Into. To end on the most positive things note possible, here is a gratuitous picture of a cat.

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Apr 142019

On the day of the umpteenth Not-So-Special Brexit Council, the stunning image of a super-massive black hole was revealed. In unrelated news, I live with two teenagers. So when idly trying to catch up on the less-than-stellar proceedings in Brussels, the headlines collided in my poor head. For posterity, here is some exclusive coverage of the incident.

A meme of Brexit as a black hole

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Mar 192018

This morning, I came across an outrageously funny a moderately amusing video involving Shaggy’s early 2000s classic, some seriously revamped lyrics, and the man himself (btw, is this blond-hairing an act of cultural appropriation?). Cheap laughs, and the almost heart-warming idea that the FBI could end this, and everything would go back to normal. And yes, they manage to squeeze a lot of legalese into these lyrics.

Which then reminded me (yes, I’m old enough to remember both the outrage over Iraq and the euphoria of Blair coming to power in 1997) of a cartoon video featuring Tony Blair, Michael Howard, and other politicians of the day, happily dancing to the same song (“I was told that there were weapons hidden underneath the sand”). I tried to google it, but it is gone, a victim of the death of flash.

What is it about this song and wildly unpopular politicians? Is there something about this song that could be coaxed into a paper (“Pseudo-Rap as Liberalism. A Conceptual Sketch and Some Applications”)? Most certainly not, so let’s just post the latest video.

Trump to Robert Mueller: 'It Wasn't Me' (w/ Shaggy)

Apr 262013

Today is clearly a day for statistical songs (are there any other days?), so here are some links to get you started.

To kick of the stat song roundup, here are some … interesting insights into the culture that is biostatics, complete with some remarkably dreadful audio material.

Obviously, you tube has a whole channel devoted to statistical songs, featuring, inter alia, Michael Greenacre, of Correspondence Analysis fame. To the true connoisseur,  it might appear a bit overproduced, but this little gem on Single Value Decomposition is very neat.

It had to be U – the SVD song

For the Structural Equation Modelling buffs, nothing compares to Alan Reifman’s annual reprise of  “SEM – the Musical”.

But for the purists, there is only one thing, something that I have watched with awe (and slowly building shock) growing beyond all expectations. The conspiracy against Frequentism have their very own book of Bayesian praise, complete with  LaTex  source, now compromising 40-odd songs including some “previously lost classic songs”, including “Bayesians in the night” (two versions, actually).


Mar 042013