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On Selecting Stable Predictors in Time Series Models by Bijral, Avleen S. is a scholarly article available to read on EtoBox.

What is On Selecting Stable Predictors in Time Series Models about?

We extend the feature selection methodology to dependent data and propose a novel time series predictor selection scheme that accommodates statistical dependence in a more typical i.i.d sub-sampling based framework. Furthermore, the machinery of mixing stationary processes allows us to quantify the improvements of our approach over any base predictor selection method (such as lasso) even in a finite sample setting. Using the lasso as a base procedure we demonstrate the applicability of our methods to simulated and several real time series datasets.

Author

Bijral, Avleen S.

Published

2019

Language

EN