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

### 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.
``` |

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