Nothing has gotten more attention in the visualization world like the map-based insights, or in other words, just plotting on a map different KPIs to allow for a playful discovery experience. I must admit,...

D Kelly O’Day did a great post on charting NASA’s Goddard Institute for Space Studies (GISS) temperature anomaly data, but it sticks with base R for data munging & plotting. While there’s absolutely nothing wrong with base R operations, I thought a modern take on the chart using dplyr, magrittr & tidyr for data manipulation

In this post I will run SAS example Logistic Regression Random-Effects Model in four R based solutions; Jags, STAN, MCMCpack and LaplacesDemon. To quote the SAS manual: 'The data are taken from Crowder (1978). The Seeds data set is a 2 x 2 fa...

Since the previous post was fairly popular, I went ahead and built a small shell script (also below) to ease the process of building the OS X Shiny-gist application. After copying the script to a place you can run it from in your PATH and executing a “chmod a+x shinyapp.sh” (or whatever you named it), all you have to...

This article was originally published in Geoinformatics magazine. R is well known as a powerful, extensible and relatively fast statistical programming language and open software project with a command line interface (CLI). What is less well known is that R also has cutting edge spatial packages that allow it to behave as a fully featured Geographical Information System...

Introduction My statistics education focused a lot on normal linear least-squares regression, and I was even told by a professor in an introductory statistics class that 95% of statistical consulting can be done with knowledge learned up to and including a course in linear regression. Unfortunately, that advice has turned out to vastly underestimate the