A new version of the OpenStreetMap package is now up on CRAN, and should propagate to all the mirrors in the next few days. The primary purpose of the package is to provide high resolution map/satellite imagery for use in your R plots. The package supports base graphics and ggplot2, as well as transformations between spatial coordinate
I was Inspired from Ben Frys all Streets project. There he plotted all streets of the United States of America (about 240 million segments). I tried this first for the countries in Europe, France has about 22 million segments, with the goal to get an all street map of Europe. My data source originate from
I was fortunate enough to have been able to attend the Amazon AWS Summit in NYC and to listen to Werner Vogels give the keynote. I will share a few of my thoughts on the AWS 2013 Summit and some of my take-aways. I attended sessions that focused on two products in particular: Redshift and
Sometimes people ask me how the examples of my plotting functions I show here can be reproduced without having a SPSS data set (or at least, without having the data set I use because it’s not public yet). So I … Weiterlesen →
Spotting international conflict is very easy with the GDELT data set, combined with ggplot and R. The simple gif above shows snapshots of Russian/Soviet activity from January 1980 and January 2000. I think it also illustrates how Russia nowadays looks more to the east and the South than during the Cold War. The trend, though...
by Thomas Dinsmore Revolution R Enterprise Release 6.2 goes live next week, so naturally our development team is thinking ahead to Release 7, which we plan to release later this year. Some of those enhancements are hush-hush, and we can't talk about them yet. But one of the most important enhancements we've already announced: support for predictive analytics inside...
(This article was first published on Quantifying Memory, and kindly contributed to R-bloggers) In this post I show how to select relevant bits of the GDELT data in R and present some introductory ideas about how to visualise it as a network map. I've included all the code used to generate the illustrations. Because of this, if you here...
This entry is part 12 of 12 in the series Using RGIS, an acronym that brings joy to some and strikes fear in the heart of those not interested in buying expensive software. Luckily fight or flight can be saved for another day because you … read more ...
I’ve been showing my new favourite toys to just about anyone foolish enough to actually engage me in conversation. I described how my shiny new set of non-transitive dice work here, complete with a map showing all the relevant probabilities. All was neat and tidy and wonderful until fellow ecologist, Aaron Ball, tried to burst 
In my never ending quest to find the perfect measure of tail fatness, I ran across this recent paper by Cooke, Nieboer, and Misiewicz. They created a measure called the “Obesity index.” Here’s how it works: Step 1: Sample four times from a distribution. The sample points should be independent and identically distributed (did your
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
