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.

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**.

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()
```

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.

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")
```

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 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")
```

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.