granova: Graphical Analysis of Variance

This small collection of functions provides what we call elemental graphics for display of analysis of variance results, David C. Hoaglin, Frederick Mosteller and John W. Tukey (1991, ISBN:978-0-471-52735-0), Paul R. Rosenbaum (1989) <doi:10.2307/2684513>, Robert M. Pruzek and James E. Helmreich <https://jse.amstat.org/v17n1/helmreich.html>. The term elemental derives from the fact that each function is aimed at construction of graphical displays that afford direct visualizations of data with respect to the fundamental questions that drive the particular analysis of variance methods. These functions can be particularly helpful for students and non-statistician analysts. But these methods should be quite generally helpful for work-a-day applications of all kinds, as they can help to identify outliers, clusters or patterns, as well as highlight the role of non-linear transformations of data.

Version:	2.2
Depends:	R (≥ 3.1.1), car (≥ 2.0-21)
Suggests:	mgcv, rgl, tcltk, MASS
Published:	2023-03-22
DOI:	10.32614/CRAN.package.granova
Author:	Frederic Bertrand [cre], Robert M. Pruzek [aut], James E. Helmreich [aut]
Maintainer:	Frederic Bertrand <frederic.bertrand at utt.fr>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	granova results

Documentation:

Reference manual:

granova.pdf

Downloads:

Package source:	granova_2.2.tar.gz
Windows binaries:	r-devel: granova_2.2.zip, r-release: granova_2.2.zip, r-oldrel: granova_2.2.zip
macOS binaries:	r-release (arm64): granova_2.2.tgz, r-oldrel (arm64): granova_2.2.tgz, r-release (x86_64): granova_2.2.tgz, r-oldrel (x86_64): granova_2.2.tgz
Old sources:	granova archive

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