sglg: Fitting Semi-Parametric Generalized log-Gamma Regression Models

Set of tools to fit a linear multiple or semi-parametric regression models and non-informative right-censoring may be considered. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value distribution as an important special case.

Version: 0.1.2
Depends: R (≥ 3.1.0)
Imports: ssym, robustloggamma, Formula, survival, methods, graphics, stats
Suggests: testthat
Published: 2017-12-05
Author: Carlos Alberto Cardozo Delgado and G. Paula and L. Vanegas
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages at>
License: GPL-3
NeedsCompilation: no
CRAN checks: sglg results


Reference manual: sglg.pdf
Package source: sglg_0.1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: sglg_0.1.2.tgz
OS X Mavericks binaries: r-oldrel: sglg_0.1.2.tgz
Old sources: sglg archive


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