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.
