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

Set of tools to fit a linear multiple or semi-parametric regression models with the possibility of non-informative random right-censoring. 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 and standard normal distributions as important special cases. Inference is based on penalized likelihood and bootstrap methods. Also, some numerical and graphical devices for diagnostic of the fitted models are offered.

Version: 0.2.2
Depends: R (≥ 3.1.0)
Imports: Formula, survival, methods, stats, AdequacyModel, ggplot2, plotly, moments, gridExtra, pracma, progress, Rcpp, plot3D, magrittr, TeachingSampling
Suggests: testthat
Published: 2022-09-04
DOI: 10.32614/CRAN.package.sglg
Author: Carlos Alberto Cardozo Delgado and G. Paula and L. Vanegas
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages at>
License: GPL-3
NeedsCompilation: no
In views: Distributions
CRAN checks: sglg results


Reference manual: sglg.pdf


Package source: sglg_0.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sglg_0.2.2.tgz, r-oldrel (arm64): sglg_0.2.2.tgz, r-release (x86_64): sglg_0.2.2.tgz, r-oldrel (x86_64): sglg_0.2.2.tgz
Old sources: sglg archive


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