Spatial Microsimulation

rakeR v0.2.1 patched

I’ve patched rakeR on CRAN to v0.2.1 to fix a couple of problems in the examples and tests, which were using old labels and failing on some machines (thanks to Derek Atherton for the feedback). I’ve also updated the documentation website to use the new pkgdown template to be consistent with other R packages, most notably the tidyverse. And, that’s about it. If you’re using v0.2.0 and are happy there are no changes to the API to worry about.

rakeR v0.2.0 on CRAN

I am absolutely delighted to announce that the latest version of rakeR, version 0.2.0, is on CRAN. You can install it in R or RStudio with: install.packages("rakeR") DOI rakeR now has a DOI. This is probably more useful for me than it is for you but nevertheless, if you use rakeR please be sure to cite it and use the DOI: https://doi.org/10.5281/zenodo.821506 Changes and improvements Speed improvements in integerise() The most noticeable change is that the integerise() step, which previously took hours on a reasonable–sized data set, now takes minutes.

Spatial microsimulation 101

I recently gave a presentation for analysts and data modellers at the Department for Work and Pensions (DWP) introducing the spatial microsimulation technique (specifically the IPF flavour), and below are the slides I used (use spacebar to navigate through the slides): Alternatively you can download the presentation as a standard html file to open in your browser. Much of the content is based on material from Spatial Microsimulation with R by Robin Lovelace and Morgane Dumont (online content | physical book) and my own rakeR package for R.

rakeR v0.1.1 released on CRAN

I’m proud to announce the initial release of rakeR, v0.1.1, has been published on CRAN! It’s licensed under the GPLv3 so you can use it for any projects you wish. Purpose The goal behind rakeR is to make performing spatial microsimulation in R as easy as possible. R is a succinct and expressive language, but previously performing spatial microsimulation required multiple stages, including weighting, integerising, expanding, and subsetting. This doesn’t even include testing inputs and outputs, and validation of the results.