Blog Archives

Spatial microsimulation 101

December 21, 2016
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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): Much of the content is based on material from Spatial Microsimulation with R by

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Simplify polygons without creating slithers

September 29, 2016
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Simplify polygons without creating slithers

When simplifying polygons it’s almost inevitable that you will generate some slither polygons or gaps between the correct polygons. For example, the following image shows two adjoining complex polygons, representing two adjoining administrative areas. Note there are no gaps between the polygons; they are contiguous (the border is between Sheffield and Barnsley LADs, by the

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rakeR v0.1.1 released on CRAN

September 19, 2016
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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

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townsendr interactive map

August 20, 2016
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This week I updated my Townsend Material Deprivation Score project. The update makes townsendr an interactive online map of deprivation that users can simply view in their browser, rather than having to download and run the R code or view only static maps. I think the result is much more intuitive and useful. Making the

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Formal informal testing of research code

January 29, 2016
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Formal informal testing of research code

When writing research code I do test my code and results, but until recently I’ve only been doing this informally and not in any systematic way. I decided it was time to change my testing habits when I noticed I had recoded a variable incorrectly despite my informal tests suggesting nothing was wrong. When I

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Dissolve polygons in R

September 3, 2015
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Dissolve polygons in R

Dissolving polygons is another fairly elementary GIS task that I need to perform regularly. With R this is can be a bit involved, but once done is fully reproducible and the code can be re-used. This post is essentially a companion piece to Clipping polygons in R; I wrote both because I often forget how

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Clipping polygons in R

September 1, 2015
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Clipping polygons in R

Clipping polygons is a basic GIS task. It involves removing unneeded polygons outside of an area of interest. For example, you might want to study all local authorities (LADs) in the Yorkshire and the Humber region but can only obtain shapefiles that contain all the LADs in the UK. Removing the LADs outside of Yorkshire

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Regression Diagnostics with R

May 12, 2014
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Regression Diagnostics with R

The R statistical software is my preferred statistical package for many reasons. It’s mature, well-supported by communities such as Stack Overflow, has programming abilities built right in, and, most-importantly, is completely free (in both senses) so that anyone can reproduce and check your analyses. R is extremely comprehensive in terms of available statistical analyses, which

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