Linear Regression Models with Finite Mixtures of Skew Heavy-Tailed Errors


This package contains a principal function that performs to estimate the parameters of a regression model considering an error that follows a finite mixture of Skew Heavy-Tailed Errors, using an analytically simple and efficient EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters.


Package: FMsmsnsReg
Type: Package
Version: 1.0
Date: 2016-03-30
License: GPL (>=2)


Luis Benites Sanchez, Rocio Paola Maehara and Victor Hugo Lachos


Basso, R. M., Lachos, V. H., Cabral, C. R., Ghosh, P., 2010. Robust mixture modeling based on scale mixtures of skew - normal distributions. Computational Statistics & Data Analysis.

Lachos, V. H., Ghosh, P., Arellano-Valle, R. B., 2010. Likelihood based inference for skew-normal independent linear mixed models. Statistica Sinica 20, 303 - 322.

See Also



#See examples for the FMsmsnReg function linked above.
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