SGB: Simplicial Generalized Beta Regression

Main properties and regression procedures using a generalization of the Dirichlet distribution called Simplicial Generalized Beta distribution. It is a new distribution on the simplex (i.e. on the space of compositions or positive vectors with sum of components equal to 1). The Dirichlet distribution can be constructed from a random vector of independent Gamma variables divided by their sum. The SGB follows the same construction with generalized Gamma instead of Gamma variables. The Dirichlet exponents are supplemented by an overall shape parameter and a vector of scales. The scale vector is itself a composition and can be modeled with auxiliary variables through a log-ratio transformation. Graf, M. (2017, ISBN: 978-84-947240-0-8). See also the vignette enclosed in the package.

Version:	1.0.1.1
Depends:	Formula
Imports:	stats, MASS, numDeriv, alabama
Suggests:	knitr, goftest
Published:	2023-12-06
DOI:	10.32614/CRAN.package.SGB
Author:	Monique Graf
Maintainer:	Monique Graf <monique.p.n.graf at bluewin.ch>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
In views:	Distributions
CRAN checks:	SGB results

Documentation:

Reference manual:	SGB.pdf
Vignettes:	SGB multivariate regression

Downloads:

Package source:	SGB_1.0.1.1.tar.gz
Windows binaries:	r-devel: SGB_1.0.1.1.zip, r-release: SGB_1.0.1.1.zip, r-oldrel: SGB_1.0.1.1.zip
macOS binaries:	r-release (arm64): SGB_1.0.1.1.tgz, r-oldrel (arm64): SGB_1.0.1.1.tgz, r-release (x86_64): SGB_1.0.1.1.tgz, r-oldrel (x86_64): SGB_1.0.1.1.tgz
Old sources:	SGB archive

Linking:

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