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.

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Description file content

Package
sglg
Type
Package
Title
Fitting Semi-Parametric Generalized log-Gamma Regression Models
Version
0.1.3
Author
Carlos Alberto Cardozo Delgado and G. Paula and L. Vanegas
Maintainer
Carlos Alberto Cardozo Delgado
Description
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.
Depends
R (>= 3.1.0)
License
GPL-3
Encoding
UTF-8
LazyData
true
RoxygenNote
6.0.1
Suggests
testthat
Imports
ssym, robustloggamma, Formula, survival, methods, graphics, stats
NeedsCompilation
no
Packaged
2018-04-15 13:08:09 UTC; Sandrita
Repository
CRAN
Date/Publication
2018-04-15 14:10:22 UTC

install.packages('sglg')

0.1.3

6 days ago

Carlos Alberto Cardozo Delgado

GPL-3

Depends on

R (>= 3.1.0)

Imports

ssym, robustloggamma, Formula, survival, methods, graphics, stats

Suggests

testthat

Discussions