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sglg
View on CRAN: Click
here
Download and install sglg package within the R console
Install from CRAN:
install.packages("sglg")
Install from Github:
library("remotes")
install_github("cran/sglg") Install by package version:
library("remotes")
install_version("sglg", "0.2.6") Attach the package and use:
library("sglg")
Maintained by
Carlos Alberto Cardozo Delgado
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-22
Latest Update: 2022-09-04
Description:
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.
How to cite:
Carlos Alberto Cardozo Delgado (2017). sglg: Fitting Semi-Parametric Generalized log-Gamma Regression Models. R package version 0.2.6, https://cran.r-project.org/web/packages/sglg. Accessed 25 Jun. 2026.
Previous versions and publish date:
0.1.0 (2017-09-22 10:36), 0.1.1 (2017-11-13 18:40), 0.1.2 (2017-12-05 22:55), 0.1.3 (2018-04-15 16:10), 0.1.4 (2019-02-20 21:40), 0.1.5 (2019-07-19 06:30), 0.1.6 (2020-04-25 16:40), 0.1.7 (2020-09-19 15:30), 0.1.8 (2020-12-01 01:30), 0.1.9 (2021-01-24 17:50), 0.1.10 (2021-09-18 06:30), 0.2.0 (2021-10-11 15:20), 0.2.1 (2022-02-21 16:20), 0.2.2 (2022-09-04 05:50), 0.2.3 (2025-11-27 21:00), 0.2.4 (2025-12-09 19:10), 0.2.5 (2025-12-19 02:10), 0.2.6 (2026-01-14 21:50)
Other packages that cited sglg R package
View sglg citation profile
Other R packages that sglg depends,
imports, suggests or enhances
Complete documentation for sglg
Functions, R codes and Examples using
the sglg R package
Some associated functions: Gu . bootglg . deBoor2 . deviance_residuals . dglg . entropy . envelope.sglg . glg . gnfit . influence.sglg . logLik.sglg . lss . order_glg . pglg . plotnpc . plotsurv.sglg . qglg . quantile_residuals . residuals.sglg . rglg . sglg . shape . smoothp . ssurvglg . summary.sglg . survglg . survival_gg .
Some associated R codes: Gu.R . aux_fs.R . blockgs.R . bootglg.R . deBoor2.R . deviance_residuals.R . dglg.R . entropy.R . envelope.sglg.R . glg.R . gnfit.R . influence.sglg.R . kmpar.R . logLik.sglg.R . lss.R . order_glg.R . pglg.R . plot.npc.R . qglg.R . quantile_residuals.R . residuals.sglg.R . rglg.R . sglg.R . shape.R . smooth_parameters.R . ssurvglg.R . summary.sglg.R . survglg.R . survival_glg.R . Full sglg package functions and examples
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