Blog Archives

Robert Hijmans on Spatial Data Analysis

May 23, 2013
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Last week at the Davis R Users’ Group Robert Hijmans gave a talk about spatial data analysis in R. Robert is a professor of biogeography at UC Davis and the author of the raster (analysis of gridded data), dismo (species distribution modeling), and geosphere (spherical trigonometry), packages. Robert’s presentation spanned topics including basic...

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Improved R Profiling Summaries

May 2, 2013
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In my last post I mentioned that I had improved on R’s summaryRprof() function with a custom function called proftable(). I’ve updated proftable() to take advantage of R 3.0.0’s ability to record line numbers while profiling. I’ve put it on github – you can get it there or below. proftable reads in a file generated by...

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FasteR! HigheR! StrongeR! – A Guide to Speeding Up R Code for Busy People

April 25, 2013
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FasteR! HigheR! StrongeR! – A Guide to Speeding Up R Code for Busy People

This is an overview of tools for speeding up your R code that I wrote for the Davis R Users’ Group. First, Ask “Why?” It’s customary to quote Donald Knuth at this point, but instead I’ll quote my twitter buddy Ted Hart to illustrate a point: I’m just going to say it.I like for loops in #Rstats,...

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Debugging Tools in R with Michael Hannon

April 18, 2013
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Debugging Tools in R with Michael Hannon

Today at Davis R Users’ Group, Michael Hannon gave a great talk on how to use R’s native debugging functions. Here are his notes and code. Introduction This is a discussion of debugging techniques in R. It is based on a paper by Roger Peng, now at Johns Hopkins University (http://www.biostat.jhsph.edu/~rpeng/docs/R-debug-tools.pdf) Focus on five functions: traceback debug browser trace recover Severity level R mainly uses...

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Demographic analysis using the `popbio` library and some other fun stuff

April 4, 2013
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Demographic analysis using the `popbio` library and some other fun stuff

This week at the Davis R Users’ Group we had a great presentation by Kara Moore O’Leary on using the popbio package to examine rare plant demographics. The following is her script run through knitr. You can download the original script and associated data here. Find out more about Kara and her work at...

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Model Selection and Multi-Model Inference

February 20, 2013
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Model Selection and Multi-Model Inference

At D-RUG this week Rosemary Hartman presented a really useful case study in model selection, based on her work on frog habitat. Here is her code run through ‘knitr’. Original code and data are posted here. (yes, I am just doing this for the flying monkey) Editor’s note: we’re giving away flying monkey dolls from our...

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Mason Earles on interfacing R with the Forest Vegetation Simulator

February 13, 2013
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Mason Earles gave a great presentation this week at Davis R Users’ Group about linking R with the Forest Vegetation Simulator (FVS). FVS is a model developed by the US Forest Service to simulate forest growth over time. It’s written in FORTRAN and has been around since the 1970s. FVS has recently gone open-source (its...

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Ryan Peek on using xts and ggplot for time-series data

February 6, 2013
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Ryan Peek on using xts and ggplot for time-series data

At Davis R Users’ Group today, Ryan Peek gave a presentation on how he takes data from his field instruments and visualizes it in R. Here are his notes. The original *.Rmd file and data can be found here SHORT HOW-TO ON USING XTS AND GGPLOT FOR TIME SERIES DATA XTS is a very helpful package...

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Steve Culman on the `plyr` Package

January 17, 2013
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At Davis R Users’ Group yesteray, Steve Culman gave us an introduction to the plyr package and how to use it to manipulate data. Here’s his presentation, and the accompanying demonstration script: Steve’s talk is based on this paper by Hadley Wickham in the Journal of Statistical Software. A lot of useful related...

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Don’t R alone! A guide to tools for collaboration with R

January 7, 2013
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Don’t R alone! A guide to tools for collaboration with R

This a brief guide to using R in collaborative, social ways. R is a powerful open-source programming language for data analysis, statistics, and visualization, but much of its power derives from a large, engaged community of users. This is an introduction to tools for engaging the community to improve your R code and collaborate with others. (Am I...

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