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

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Description

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.

Details

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

Author(s)

Luis Benites Sanchez lbenitesanchez@gmail.com, Rocio Paola Maehara rmaeharaa@gmail.com and Victor Hugo Lachos hlachos@ime.unicamp.br

References

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

FMsmsnReg

Examples

1
#See examples for the FMsmsnReg function linked above.