Sharing my findings

With the current vocabulary, I will say that I am a “data scientist”, i.e. a scientist who plays with data. This website is my modest participation in sharing science… I write blog articles with R scripts in it, mainly with maps and spatial data.
There are also things related to marine science, spatialized data modeling, Bayesian models, some achievements with R-shiny and other things to share…
Some scripts are supplemental material for my scientific publications.

Open-source projects

I have some personal open-source projects.
As a former researcher, I decided to share my R-scripts as R libraries. I cannot say these respect all packages development standards but at least the code is available. Have a look at the following packages:

  • {SDMSelect}: 1. Covariate selection procedures on GLM and GAM. 2. Species distribution modelling.
  • {GeoDist}: 1. Calculate distances between points when there are obstacles. 2. Modifications of {geoR} functions to allow for custom distances.

I also use Hugo for this website, which made me work on my own template:

Other projects are available on my Github account.

Who am I?

I am a business unit director at ThinkR, a company where we answer all your questions with R, offering training, development, installation and consultancy in everything around R.

Deep inside, I am a scientist. Indeed, I have a master in agronomy and a PhD in marine biology. But data analysis and R diverted me a little from my original objectives. I left the world of marine biology research to join ThinkR. As a result, I continue to share my knowledge through trainings and open-source development. I still do data analysis and visualization, mostly through consultancy, while sharing development good practices. And I love it! I play with the cards regularly, but I don’t really adjust patterns anymore. That said, I still have material to fill this blog and share my findings and other tips with you. On R mainly!
If you are curious about what we can do with spatial tools on non-geographical data, have a look at my category “geohacking”.

Enjoy your reading!

Sébastien Rochette

3D visualisation of a meristem of Arabidopsis thaliana rendered with {rayshader}

Figure 1: 3D visualisation of a meristem of Arabidopsis thaliana rendered with {rayshader}

Jeff Leek, on simplystatistics.org

If every method in every stats journal was implemented in a corresponding R package (easy), was required to have a companion document that was a tutorial on how to use the software (easy), included a reference to how to cite the paper if you used the software (easy) and the paper/tutorial was posted to the relevant message boards for the communities of interest (easy) that journal would see a dramatic bump in its impact factor.