tslars-package {tslars}R Documentation

The tslars package performs variable selection for high-dimensional linear time series models.

Description

The tslars packages applies a dynamic variable selection procedure. It is an extension of the LARS algorithm of Efron et al (2004) which is designed for time series analysis. It provides a ranking of the predictors and a selection of which predictors to include in the final model as well as a selection of the appropriate lag length.

Details

Package: tslars
Type: Package
Version: 1.0
Date: 2009-02-06
License: gpl
LazyLoad: yes

The most improtant functions are tslars and tslars.p.

Author(s)

Sarah Gelper Maintainer: Sarah Gelper <gelper@ese.eur.nl>

References

Gelper, S. and Croux, C. (2009) Time series least angle regression for selecting predictive economic sentiment series. www.econ.kuleuven.be/sarah.gelper/public


[Package tslars version 1.0 Index]