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in 2012, more than one quarter of the united states population lived in the jurisdiction of a police department that submitted details about every crime to a central repository maintained by the fbi.  a production of the uniform crime reports (ucr) program, the national incident-based reporting system (nibrs) compiles statistics from ... [Read more...]

I would be delighted to co write a post (Andrew Wyer) One of the best things about writing a blog is that occasionally you get to know very interesting people. Last October 13th I published this post about the harmonograph, a machine driven by pendulums which creates amazing curves. Two ... [Read more...]

In this short post, I benchmark different “versions” of R. I compare the execution speeds of R, R linked against OpenBLAS, R linked against ATLAS and Revolution R Open. Revolution R Open is a new open source version of R made by Revolution Analytics. It is linked against MKL and ... [Read more...]

Cross-posted from the Software Carpentry Blog. For the past two years I’ve run the UC Davis R Users’ Group (D-RUG). In this post, I’ll (1) outline the structure of D-RUG, and (2) summarize some lessons learned, and (3) discuss how such users’ groups could act to support and complement SWC’s ... [Read more...]

If you have ever worked with US government data or other large datasets, it is likely you have faced fixed-width format data. This format has no delimiters in it; the data look like strings of characters. A separate format file defines which columns of data represent which variables. It seems ... [Read more...]

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Rcpp11 3.1.2.0 was released to CRAN, as the ultimate C++11 companion to R 3.1.2 on which it depends. The NEWS extract follows:

# Rcpp11 3.1.2

* New `wrap` implementation for `std::tuple<Args...>` (#195)

* `colnames` and `rownames` setters for matrices (#210). 

* Most sugar functions are now processing the expression in parallel. 

* Forbidden symbols from the C/R API are no longer directly used, so packages can use Rcpp11 without getting the NOTE as before.

This release marks departure from compromision. Rcpp11 used to compromise on the meaning of C++11 to satisfy platforms for which the available tooling was laging behind, most notoriously windows ... [Read more...]

Changes Version 1.4.1 of RSiteCatalyst is now available on CRAN. There were a handful of bug fixes and new features added, including: Fixed bug in QueueRanked function where only 10 results were returned when requesting multiple element reports. Function now returns up to 50,000 per breakdown (API limit) Created better error message to ... [Read more...]

We recently shared some benchmarks for Revolution R Open on the Windows platform, which showed significant improvements compared to R downloaded from CRAN. Those performance gains mainly come from multi-threading: Revolution R Open is linked to the Intel Math Kernel Library, which uses all available cores (rather than just one ... [Read more...]

Following the previous post on Rasmus’ socks, I took the opportunity of a survey on ABC I am currently completing to compare the outcome of his R code with my analytical derivation. After one quick correction [by Rasmus] of a wrong representation of the Negative Binomial mean-variance parametrisation [by me], ... [Read more...]

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A new release of BH, our package providing Boost headers for use by R is now on CRAN. This release was triggered via a request by Ben Goodrich as noted below who asked for Boost Circular Buffer which RStan uses. No other changes were made. Changes ... [Read more...]

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And I had to do it again: I am using R installed from homebrew, and after the upgrade from Mavericks to Yosemite, I had to re-install all packages – or was it a GCC upgrade? I don’t know – but I had to do it again. I still had the link ... [Read more...]

Why open data growth At rOpenSci we try to make it easier for people to use open data and contribute open data to the community. The question often arises: How much open data do we have? Another angle on this topic is: How much is open data growing? We provide ... [Read more...]

Introduction Solar altitude is a function of time, longitude and latitude, and so it can be possible to infer location based on measuring altitude as a function of time. This form of solar navigation can be based on sunrise and sunset times, at least on non-equinox days. I have explored ... [Read more...]

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