New release of pqR, with a curated repository

2014-06-21 at 10:59 pm 2 comments

I have released a new version, pqR-2014-06-19, of my speedier, “pretty quick”, implementation of R.  This and the previous release (pqR-2014-02-23) are maintenance releases, with bug fixes, improved documentation, and better test procedures.

The result is that pqR now works with a large collection of 3438 packages.

This collection was created starting with the complete set of CRAN packages as of 2012-06-25. Packages were then eliminated if they were not suitable for Linux, or if their licence was unacceptable, or if they failed their checks with R-2.15.0 (on which pqR is based) as well as with pqR (though sometimes a more recent version of the package that works was found), or if they required Linux software that wasn’t easily installed. Also, some packages were added, and some upgraded to more recent versions, in order to produce a collection of packages that all pass their checks if the entire set of packages is first installed from this repository. Finally, a few packages from bioconductor.org were added.

See the pqR wiki for more information on how to access this repository, and for more information on packages that do and do not work with pqR .

The process of creating this curated repository revealed a number of bugs in pqR, which have now been fixed. I now know of no packages that fail because of what appears to be a pqR bug. This repository of packages that all work together should be a valuable resource for testing future versions of pqR. Some features have been added to pqR to facilitate this use, such as initializing the random number seed (if not set by set.seed) from the R_SEED environment variable (if it is set), rather than initializing the seed from the time and process id, which leads to random failures of checks for some packages.

Some of the bugs fixed in this release were introduced by changes made in pqR, others are present in the R Core version pqR is based on and in the latest R Core release, R-3.1.0.  Some of the documentation improvements provide information that is missing or incorrect in R-3.1.0.  See the pqR NEWS for details.

With this release, I think the reliability of pqR is comparable to that of recent R Core releases.  There is still work to be done to improve compatibility by incorporating features introduced in R Core releases after 2.15.0.  However, the main focus of the next release will be further performance improvements.

Entry filed under: Computing, R Programming, Statistics, Statistics - Computing.

Inaccurate results from microbenchmark Brixen / Bressanone, Italy, June 2014

2 Comments Add your own

  • 1. Jason Liao  |  2014-06-23 at 7:38 am

    I hope that the innovation in pqR will soon be incorporated by R core in the standard R distribution as most statisticians do not have the technical skills to compile their own R.

    Reply
    • 2. G  |  2014-07-21 at 9:42 pm

      That is up to the R core team, you should ask them about it. I recall that Radford initially tried to contribute patches to R instead of making pqR.

      Reply

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