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.

Version: 1.5.7
Depends: GIGrvg, numDeriv, normalp, Formula, survival
Imports: stats, grDevices, sandwich, graphics, methods, utils
Suggests: NISTnls, gam, sn, MASS
Published: 2016-10-16
Author: Luis Hernando Vanegas and Gilberto A. Paula
Maintainer: Luis Hernando Vanegas <hvanegasp at gmail.com>
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: ssym results

Downloads:

Reference manual: ssym.pdf
Package source: ssym_1.5.7.tar.gz
Windows binaries: r-devel: ssym_1.5.7.zip, r-release: ssym_1.5.7.zip, r-oldrel: ssym_1.5.7.zip
OS X El Capitan binaries: r-release: ssym_1.5.7.tgz
OS X Mavericks binaries: r-oldrel: ssym_1.5.7.tgz
Old sources: ssym archive

Reverse dependencies:

Reverse imports: sglg
Reverse suggests: BayesGESM

Linking:

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