Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended

For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.


Description

In order to use the extended functions of the R package PMCMRplus, several additional R packages available from CRAN need to be imported, i.e. mvtnorm (Genz and Bretz and 2009, Genz et al. 2015), multcompView (Graves et al. 2015), Rmpfr (Maechler 2016) and gmp (Lucas et al. 2017). This will be done automatically by R's package management system.

However, Linux user may encounter some installation problems, as several R packages require external libraries on the system. This is why this README file briefly describes the installation procedure of PMCMRplus.

Installation under Windows

As R packages for Windows are distributed in binary form, there should not be any problem with the installation. Simply run from within R the following function:

install.packages("PMCMRplus")

R will automatically install all the relevant dependencies. Provided that PMCMRplus is already installed on your system, simply update the package or all installed packages with: update.packages("PMCMRplus")

# or update all
update.packages()

Installation under Linux from source packages

R packages for Unix / Linux are distributed in source form. Installation of R add-on packages do not require root proviliges and the installation directory is set in the variable $R_LIBS_USER. The installation directory is in the users $HOME directory.

First check, whether PMCMRplus can be installed or updated by running the following function from within R:

# update PMCMRplus
update.packages("PMCMRplus")

# or install
install.packages("PMCMRplus")

Both R packages Rmpfr and gmp need compilation and are wrapper functions for the external libraries (i.e. not shipped with R) libmpfr (Fousse et al. 2007, http://www.mpfr.org/) and libgmp (https://gmplib.org/). For a correct compilation, the corresponding header files of the external libraries are required. Therefore, it is possible that the installation process breaks up with an error message such as:

...
configure: error: GNU MP not found ...
...
configure: error: Header file mpfr.h not found

However, both libraries and their header files are commonly available on various Linux distributions.

Ubuntu and Debian

Check for the header files by running the following commands outside of R from the console.

dpkg -p libgmp-dev
dpkg -p libmpfr-dev

If any (or both) of the above packages are missing, simply install the missing package(s) from the repository of your Linux distribution:

sudo apt-get install libgmp-dev
sudo apt-get install libmpfr-dev

After successful installation of the above Linux packages, repeat with the installation of the R package PMCMRplus from within R:

install.packages("PMCMRplus")

Fedora, Redhat, CentOS, opensuse, etc.

Check for the header files by running the following commands outside of R from the console.

dnf info gmp-devel
dnf info mpfr-devel

If any (or both) of the above packages are missing, simply install the missing package(s) from the repository of your Linux distribution:

sudo dnf install gmp-devel
sudo dnf install mpfr-devel

After successful installation of the above Linux packages, repeat with the installation of the R package PMCMRplus from within R:

install.packages("PMCMRplus")

Installation under Linux using binary packages

Ubuntu

Installation instructions for R core using an Ubuntu distribution can be found here:

https://cran.r-project.org/bin/linux/ubuntu/

Additional CRAN binary packages (>1,000) for Ubuntu are availabe at the CRAN2deb4ubuntu PPA that can be found here

https://launchpad.net/~marutter/+archive/ubuntu/c2d4u

or

https://launchpad.net/~marutter/+archive/ubuntu/c2d4u3.5.

Provided, that the above PPA was successfully added to the package source list and the user has root (or su, sudo) priviliges, one can try to install precompiled r-cran* deb packages outside of the R environment as

sudo apt-get install r-cran-rmpfr
sudo apt-get install r-cran-gmp

As by the time of writing of this README the package PMCMRplus was not yet converted into a deb package by the PPA maintainer, the user must install the package from within R as:

install.packages("PMCMRplus")

References

L. Fousse, G. Hanrot, V. Lefevre, P. Pelissier, P. Zimmermann (2007) MPFR: A Multiple-precision Binary Floating-point Library with Correct Rounding. ACM Trans. Math. Softw. 33. 13. http://doi.acm.org/10.1145/1236463.1236468.

A. Genz, F. Bretz (2009) Computation of Multivariate Normal and t Probabilities. Lecture Notes in Statistics. Heidelberg: Springer.

A. Genz, F. Bretz, T. Miwa, X. Mi, F. Leisch, F. Scheipl, T. Hothorn (2017) mvtnorm: Multivariate Normal and t Distributions. R package version 1.0-6, https://CRAN.R-project.org/package=mvtnorm.

S. Graves, H.-P. Piepho, L. Selzer, S. Dorai-Raj (2015) multcompView: Visualizations of Paired Comparisons. R package version 0.1-7, https://CRAN.R-project.org/package=multcompView.

A. Lucas, I. Scholz, R. Boehme, S. Jasson, M. Maechler (2017) gmp: Multiple Precision Arithmetic. R package version 0.5-13.1, https://CRAN.R-project.org/package=gmp.

M. Maechler (2016) Rmpfr: R MPFR - Multiple Precision Floating-Point Reliable. R package version 0.6-1. https://CRAN.R-project.org/package=Rmpfr.

News

Reference manual

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install.packages("PMCMRplus")

1.4.1 by Thorsten Pohlert, 7 months ago


Browse source code at https://github.com/cran/PMCMRplus


Authors: Thorsten Pohlert


Documentation:   PDF Manual  


GPL (>= 3) license


Imports mvtnorm, multcompView, gmp, Rmpfr, SuppDists, kSamples, BWStest, MASS

Suggests xtable, graphics, knitr, rmarkdown, car, e1071, multcomp, pwr

System requirements: gmp (>= 4.2.3), mpfr (>= 3.0.0) | file README.md


Imported by easyDes.


See at CRAN