ssym

Fitting Semi-Parametric log-Symmetric Regression Models

Set of tools to fit a semi-parametric regression model suitable for analysis of data sets in which the response variable is continuous, strictly positive, asymmetric and possibly, censored. Under this setup, both the median and the skewness of the response variable distribution are explicitly modeled by using semi-parametric functions, whose non-parametric components may be approximated by natural cubic splines or P-splines. Supported distributions for the model error include log-normal, log-Student-t, log-power-exponential, log-hyperbolic, log-contaminated-normal, log-slash, Birnbaum-Saunders and Birnbaum-Saunders-t distributions.

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Description file content

Package
ssym
Type
Package
Title
Fitting Semi-Parametric log-Symmetric Regression Models
Version
1.5.7
Date
2016-10-15
Author
Luis Hernando Vanegas and Gilberto A. Paula
Maintainer
Luis Hernando Vanegas
Description
Set of tools to fit a semi-parametric regression model suitable for analysis of data sets in which the response variable is continuous, strictly positive, asymmetric and possibly, censored. Under this setup, both the median and the skewness of the response variable distribution are explicitly modeled by using semi-parametric functions, whose non-parametric components may be approximated by natural cubic splines or P-splines. Supported distributions for the model error include log-normal, log-Student-t, log-power-exponential, log-hyperbolic, log-contaminated-normal, log-slash, Birnbaum-Saunders and Birnbaum-Saunders-t distributions.
License
GPL-2 | GPL-3
Depends
GIGrvg, numDeriv, normalp, Formula, survival
Imports
stats, grDevices, sandwich, graphics, methods, utils
Suggests
NISTnls, gam, sn, MASS
Packaged
2016-10-16 01:58:56 UTC; Usuario
NeedsCompilation
no
Repository
CRAN
Date/Publication
2016-10-16 09:44:42

install.packages('ssym')

1.5.7

02 years ago

Luis Hernando Vanegas

GPL-2 | GPL-3

Depends on

GIGrvg, numDeriv, normalp, Formula, survival

Imports

stats, grDevices, sandwich, graphics, methods, utils

Suggests

NISTnls, gam, sn, MASS

Discussions