Franchu’s Lair

Last week I was in Poznan, Poland for a workshop and had a great time there. The city is really nice with its old city center and as soon as you get out of it you can still feel the communist past of the country. All in all a great experience for a westerner.

We sampled a few pubs and I recommend the following:

• Brovaria: A nice restaurant/bar with its own brewery. They have wheat beer, normal beer and honey beer, plus a selection of good food.
• Dragon: A cool place with lots of wooden stairs around a central patio. It looks like a castle
• Johnny Rocker: Quiet place near the square. Good place to set a meeting point while enjoying a glass of Ziwiec or Lech (Polish beers)

You can see some of the photos of the city and the workshop:

Con frecuencia cuando escribimos en LaTeX nos encontramos con el problema de que no sabemos cómo se escribe un determinado símbolo matemático, y acabamos perdiendo muchísimo tiempo describiendo el símbolo en Google, o mirando interminables tablas de símbolos hasta dar con el que realmente queremos usar.

Afortunadamente, ahora ya no hace falta complicarse la vida Existe una página en la que podemos dibujar nosotros mismos el símbolo y automáticamente proporciona sugerencias del símbolo que hemos querido pintar y cómo escribirlo en LaTeX.

Yo era un poco escéptico, pero la verdad es que funciona muy bien. Da gusto ver que el reconocimiento de patrones en 2D sigue desarrollándose a toda velocidad y que empiezan a aparecer aplicaciones útiles y sencillas de utilizar para el gran público.

During GEOSTAT2009 earlier this year, I had the pleasure to meet Professor Roger Bivand, a british geographer teaching in a norwegian economics schools who was kind enough to spend a week in Croatia sharing his knowledge on geostatistics with us.

He is one of the authors of the sp package for R and he has a very good overview of the state-of-the-art on geostatistics.

The last day of the course, I proposed him to run a short interview on my blog and he accepted. His answers came very fast to my mailbox, but it took me way too long to sit down and write them in this post.

I would like to thank Roger for his kind answers, and I hope you will enjoy reading them as much as I did.

As one of the main developers of the sp package , what was your motivation to do it?

It’s mostly described in a talk I gave at DSC’03 in Vienna although the actual sketch was made on an excursion at the StatGIS meeting later the same year, at which Edzer Pebesma and Virgilio Gómez Rubio were also present, and where Albrecht Gebhardt was a local organiser.

The idea is not so much to provide a single standard representation, but to be open to interfacing with other representations, so that exchanging data may be made easier.

Has SpatialData (and their related structures) become the standard to represent spatial information in R? If any, which are the alternatives?

The large number of packages that depend on or suggest sp indicates that others find the representations useful. Other representations include those in the maps, PBSmapping, and spatstat packages among others – most are listed on the CRAN “Spatial” Task View.

Is it possible to contribute to the sp package or it is a piece of work that is complete and just maintained by a selected few?

The package source is (still) hosted on the r-spatial project on sourceforge. Contributions are welcome, but their incorporation is the responsibility of the authors, so it may be suggested that a separate package is more appropriate. I guess “select few” is not inappropriate, but that’s just the way things have happened.

What would you like to see implemented in the sp package that is still not there?

After four implementations of rings and polygons as something like a shapefile, it might be worth looking at an OGC Simple Features representation instead, otherwise nothing much on the TODO list.

Lately there has been a lot of talking about R (it got even an article on the New York Times) Have you noticed an increase on the interest on the sp package and the spatial capabilities of R?

There is a good deal of interest, witnessed by the number of subscribers on R-SIG-GEO, and offlist email traffic. But interest in itself isn’t interesting, it’s the quality of the new ideas and good bug reports that keeps the momentum up.

As the person who runs the R-SIG-GEO mailing list, how would you describe the community there? What are your plans (if any) for the mailing list?

There are an increasing number of “helpers” – subscribers who both start new threads and reply to questions in existing threads – it would be nice to see that trend continue and strengthen. It seems important to help subscribers to express themselves clearly – some problems are seen rather differently in other disciplines. I don’t have plans beyond trying to answer well-framed questions as they are posted, something which can take a good chunk of my day. I can feel guilty if someone has to wait, or doesn’t get an answer, but know that this isn’t a sustainable model, others can often answer better than I could.

As a geographer working in an economics school, you have a solid background on geography and statistics. What would be the baby steps that you would recommend to people lacking such a background to get initiated in the field of geostatistics up to the level in which they can follow the ASDAR book?

This is hard to answer, as people vary a lot. Some like to study a book or books – many are indicated in the ASDAR book, at different levels. Others are driven by a research question, others again learn through examples. Probably the only shared characteristic would be that these are things you can’t really get unmotivated people to grasp, but if someone is motivated, they’ll find their way in somehow. And enjoy it, after all, it is supposed to be fun, isn’t it?

Geostatistics is a relatively recent field and some of the calculations have been only possible in the last years thanks to the development of cheap computing power. Supposing that computing power and memory are not an issue… what do you think would be the next developments in the geostatistics world? (4D interpolation/prediction? local geostatistics?)

Hard to say, but probably more model-based geostatistics and conditional simulation (making the best use of limited data). Beyond that, I think that before 4D or even 3D, we should expect more movement on geostatistics for non-continuous data (count data and presence/absence data), something like GLMM models, and most likely hierarchical models capable of doing something sensible with zero inflation, which dogs many research problems. In fact, getting statisticians involved in helping design data collection is more likely to yield better results than more compute power.

One of the biggest challenges we need to resolve is related to information visualisation. The outputs of the calculations need to be easily understandable by others. Do you think that R is the right place to develop new visualisations or would it be better to export/communicate the data to other applications in which visual designers feel more comportable?

If we are thinking about analytical and exploratory visualisation, then yes, R is an appropriate place, not least because a lot of the research on statistical graphics and data visualization is done in R. Dynamic linked graphics with zooming are not easy, and will take time to do in a cross-platform way, so maybe there, other software environments may be prefered. The current graphics model in R is under constant development, with the newer achievement including anti-aliassing and proper use of the alpha channel where possible. This is also linked to attempts to provide proper graphics support for UTF-8, which is harder than one might think. A lot is going on at the moment in these areas, but time will tell which innovations succeed and diffuse.