Time varying regression with hidden linear dynamics
Statistics Theory
2022-01-03 v1 Optimization and Control
Machine Learning
Statistics Theory
Abstract
We revisit a model for time-varying linear regression that assumes the unknown parameters evolve according to a linear dynamical system. Counterintuitively, we show that when the underlying dynamics are stable the parameters of this model can be estimated from data by combining just two ordinary least squares estimates. We offer a finite sample guarantee on the estimation error of our method and discuss certain advantages it has over Expectation-Maximization (EM), which is the main approach proposed by prior work.
Cite
@article{arxiv.2112.14862,
title = {Time varying regression with hidden linear dynamics},
author = {Ali Jadbabaie and Horia Mania and Devavrat Shah and Suvrit Sra},
journal= {arXiv preprint arXiv:2112.14862},
year = {2022}
}
Comments
22 pages