New Fedora Core RPMS for CRAN packages arm, Matrix, lme4, car, coda, leaps, and mlmRev

Posted by Tom Moertel Wed, 25 Apr 2007 18:07:00 GMT

Just a quick note for folks using the R statistics system on Fedora Linux. I have packaged for Fedora a bunch of R packages from the CRAN. (R packages have to be packaged again, as RPM packages, to integrate with Fedora Linux.)

My initial goal was to package arm, which contains tools for working with various regression models. (This package accompanies Andrew Gelman and Jennifer Hill’s wonderful book Data Analysis Using Regression and Multilevel/Hierarchical Models.) Packaging “arm,” however, quickly snowballed into packaging a bunch of prerequisites. Thankfully, I have now completed that task and can share the fruits of my labor with you.

All in all, to install “arm,” you will need the following RPMs:

  • R-arm-1.0-2
  • R-car-1.2-1
  • R-lme4-0.9975-1
  • R-Matrix-0.9975-1
  • R-R2WinBUGS-2.0-1

The following RPMs are optional (but you will need them if you want to rebuild the RPMs):

  • R-coda-0.10-1
  • R-leaps-2.7-1
  • R-mlmRev-0.995-1

You can download the packages from the RPMs section of the Community Projects site. Better yet, you can use Yum to download them for you. Just add the moertel-community Yum repository to your /etc/yum.repos.d directory (see RPMs for the recipe) and then use the following command:

$ sudo yum install R-arm

Yum will automatically resolve dependencies and install the required packages. If you want any of the optional packages, add them after “R-arm” on the command line.

I have built the packages for Fedora Core 6 on the x86_64 architecture, but the RPM specs are available if you want to rebuild the packages for other architectures. (See the instructions for rebuilding RPMs for help.)

Caveat: I’m not sure that the R-R2WinBUGS package is fully functional. It depends on BRugs, which doesn’t yet build on the Linux platform. To get around this problem, I made R-R2WinBUGS’s dependency on BRugs weak; the first package no longer requires the second to install.

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Engauge Digitizer: a handy tool for extracting data from charts

Posted by Tom Moertel Tue, 17 Apr 2007 07:45:00 GMT

Today I wanted to extract the data that were visualized in a chart I saw on Seth Roberts’s blog. That is, I had a picture of a data set, and I wanted the numbers behind the picture.

This task turned out to be surprisingly easy – once I found Engauge Digitizer, an open-source (GPL) tool made for this very task. After I launched Engauge, the digitization process was straightforward:

  1. I established the chart’s coordinate system by clicking in the corners and entering the associated coordinates.
  2. Then I had Engauge identify data points. With the mouse, I selected a data point by hand, teaching Engauge what a point looks like. Then Engauge identified spots on chart that looked like data points and locked on to them. I was able to step through the points to tell Engauge to skip the few it misidentified.
  3. I manually selected a few more data points that were scrunched into blobs and had eluded Engauge’s point-detection heuristics.
  4. Finally, I exported the data set in CSV format.

If you ever need to extract the data behind a chart, do check out Engauge Digitizer. (If you use Fedora Linux, you’ll be happy to know that I have packaged Engauge for you. Get it at the RPMs section of the community site.)

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