ssym: Fitting Semi-parametric Log-symmetric Regression Models

This package allows to to fit a semi-parametric regression model suitable for analysis of data sets in which the response variable is continuous, strictly positive, and asymmetric. In this setup, both median and skewness of the response variable distribution are explicitly modeled through semi-parametric functions, whose nonparametric 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: 1.5.2
Depends: GIGrvg, numDeriv, splines, normalp, Formula
Suggests: NISTnls, gam, sn
Published: 2015-01-08
Author: Luis Hernando Vanegas and Gilberto A. Paula
Maintainer: Luis Hernando Vanegas <hvanegasp at>
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: ssym results


Reference manual: ssym.pdf
Package source: ssym_1.5.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: ssym_1.5.2.tgz, r-oldrel: ssym_1.5.2.tgz
OS X Mavericks binaries: r-release: ssym_1.5.2.tgz
Old sources: ssym archive

Reverse dependencies:

Reverse suggests: BayesGESM