The tslars package performs variable selection for high-dimensional linear time series models.
tslars包进行高维非线性时间序列模型的变量选择。
译者:生物统计家园网 机器人LoveR
描述----------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.
tslars包适用于动态变量的选择过程。它是一个扩展的LARS埃夫隆等人(2004)的算法,其目的是为时间序列分析。它提供了一个排名的预测和选择,包括在最终的模型,以及选择适当的滞后长度的预测。
Details
详细信息----------Details----------
</table> The most improtant functions are tslars and tslars.p.
</ TABLE>:最重要的功能是tslars和tslars.p。
(作者)----------Author(s)----------
Sarah Gelper
Maintainer: Sarah Gelper <gelper@ese.eur.nl>
参考文献----------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
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。