HEAVY: Robust estimation using heavy-tailed distributions
The HEAVY package contains routines
to perform robust estimation considering heavy-tailed distributions. Currently,
the package includes linear regression, linear mixed-effect models, Grubbs'
model, multivariate location and scatter estimation, multivariate regression,
penalized splines, random variate generation and some support functions.
Provide basic functionality for modeling using scale mixtures of normal distributions in R, via a package.
Calculations associated with parameter estimation are performed by calling routines in C and Fortran.
Estimation in linear regression, linear mixed effects models, Grubbs' model, multivariate regression and penalized splines using the EM algorithm.
Estimation of location and Scatter using multivariate heavy-tailed distributions.
Implemented families: normal, Cauchy, Student-t, slash and contaminated normal.
Estimation of the shape parameters for Student-t and slash distributions.
Multivariate random number generation for the implemented families and the uniform distribution on the p-dimensional sphere.
Print and summary methods and some sample databases.
Please report any bugs/suggestions/improvements to Felipe
Osorio, Universidad Técnica Federico Santa María. If you find these
routines useful or not then please let me know. Also, acknowledgement of the use of the
routines is appreciated.
Alternatively, you can download the source as a tarball or as a zip file.
Unpack the tarball or zipfile (thereby creating a directory named, heavy)
and install the package source by executing (at the console prompt)
Next, you can load the package by using the command: library(heavy)
The package is provided under the GPL. HEAVY is under active development: new features are
being added and old features are being improved. Although the developer will
make efforts to preserve backward compatibility, we cannot absolutely guarantee