ssym (1.5.7)

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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.

Maintainer: Luis Hernando Vanegas
Author(s): Luis Hernando Vanegas <> and Gilberto A. Paula

License: GPL-2 | GPL-3

Uses: Formula, GIGrvg, normalp, numDeriv, sandwich, survival, NISTnls, gam, sn, MASS
Reverse suggests: BayesGESM

Released over 3 years ago.

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