Felix Schönbrodt

PD Dr. Dipl.-Psych.

Installation of WRS package (Wilcox’ Robust Statistics)

Update Feb 17, 2014: WRS moved to Github – This installation procedure has been updated and still is valid

Some users had trouble installing the WRS package from R-Forge. Here’s a method that should work automatically and fail-safe:

# first: install dependent packages
install.packages(c("MASS", "akima", "robustbase"))

# second: install suggested packages
install.packages(c("cobs", "robust", "mgcv", "scatterplot3d", "quantreg", "rrcov", "lars", "pwr", "trimcluster", "parallel", "mc2d", "psych", "Rfit"))

# third: install an additional package which provides some C functions

# fourth: install WRS
install_github("nicebread/WRS", subdir="pkg")

WRS cannot be hosted on CRAN, as CRAN demands help files for every user-visible function. This has not been done for WRS (yet). For the time being, this somewhat more complicated installation routine has to be used.

Further thoughts on post-publication peer review (PPPR)
At what sample size do correlations stabilize?
Comments (14) | Trackback

14 Responses to “Installation of WRS package (Wilcox’ Robust Statistics)”

  1. Peter Ellis says:

    Hi – doesn’t seem to work at the moment (July 2013). Has it been locked off?

  2. FelixS says:

    Yup, R-Forge is down until 12 July 2013: http://r-forge.r-project.org/forum/forum.php?forum_id=4407
    If you can’t wait, download the functions from http://dornsife.usc.edu/labs/rwilcox/software/

  3. Heidi says:

    Hi Felix, just to say many thanks for the helpful code.

  4. […] [Update Aug 2013: For a fail safe installation routine, see this up-to-date post: Installation of the WRS package] […]

  5. […] For a fail-safe installation of the package, follow this instruction. […]

  6. FelixS says:

    Update Sep 19 (v. 0.23.2): Due to an error in the NAMESPACE file the functions were not exported. Works with 0.23.2.

  7. […] from the WRS package compares user-defined quantiles of both distributions using a Harrell–Davis estimator in conjunction with a percentile bootstrap. The method seems to improve over other methods: “Currently, when there are tied values, no other method has been found that performs reasonably well. Even with no tied values, method HD can provide a substantial gain in power when q ≤ .25 or q ≥ .75 compared to other techniques that have been proposed”. The method is described in the paper “Comparing two independent groups via the upper and lower quantiles” by Wilcox, Erceg-Hurn, Clark and Carlson (2013). You can use the function as soon as you install the latest version of the WRS package following this installation instruction. […]

  8. […] Update: For installation of the WRS package, please use only the fail-safe installation procedure described here! […]

  9. Shu Fai says:

    Thanks for the instruction. Just a simple question. I noticed that there is also a project called WRScppWin. If I run R for Windows, should I install that package instead of WRScpp?

  10. ThomasB says:

    Dear FelixS, I’ve been trying to install WRS on R 3.1.1 (on MacOS), following your highly useful method above, but to no avail. None of the WRS functions (e.g. t2way) is recognised, even though library(WRS) does not yield any error messages. Do you think there may be any problem with my R version (which is the most recent one, as far as I know).
    Thanks a lot!

  11. Maggie says:

    Can’t seem to get this to work for R 3.1.2, is it compatible?

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