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Simone Vazzoler edited this page Oct 19, 2016 · 4 revisions

Welcome to the sparsevar wiki!


sparsevar is an R package that estimates sparse VAR and VECM model using penalized least squares methods (PLS): it is possible to use various penalties such as ENET, SCAD or MC+ penalties. The sparsity parameter can be estimated using cross-validation or time slicing. When using ENET it is possible to estimate VAR(1) of dimension up to 200, while when using one of the other two is better not to go beyond 50. When estimating a VAR(p) model then the limits are roughly 200/p and 50/p, respectively. The authors of sparsevar are Monica Billio, Lorenzo Frattarolo and Simone Vazzoler and the R package is mantained by Simone Vazzoler. This wiki describes the usage of sparsevar in R.

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