Time varying regression with hidden linear dynamics

• URL: http://arxiv.org/abs/2112.14862v1
• Date: Wed, 29 Dec 2021 23:37:06 GMT
• Title: Time varying regression with hidden linear dynamics
• Authors: Ali Jadbabaie, Horia Mania, Devavrat Shah, Suvrit Sra
• Abstract summary: 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.
• Score: 74.9914602730208
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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