Driver Estimation in Non-Linear Autoregressive Models

Tom Dupré la Tour; Yves Grenier; Alexandre Gramfort

ICASSP 2018accepted0 citations

Driver Estimation in Non-Linear Autoregressive Models

Tom Dupré la Tour, Yves Grenier, Alexandre Gramfort

Abstract

In non-linear autoregressive models, the time dependency of coefficients is often driven by a particular time-series which is not given and thus has to be estimated from the data. To allow model evaluation on a validation set, we describe a parametric approach for such driver estimation. After estimating the driver as a weighted sum of potential drivers, we use it in a non-linear autoregressive model with a polynomial parametrization. Using gradient descent, we optimize the linear filter extracting the driver, outperforming a typical grid-search on predefined filters.

BibTeX

@inproceedings{icassp2018_driverestimation,
  title = {Driver Estimation in Non-Linear Autoregressive Models},
  author = {Tom Dupré la Tour and Yves Grenier and Alexandre Gramfort},
  booktitle = {ICASSP 2018},
  year = {2018}
}