Model Agnostic Time Series Analysis via Matrix Estimation

<jats:p>We propose an algorithm to impute and forecast a time series by transforming the observed time series into a matrix, utilizing matrix estimation to recover missing values and de-noise observed entries, and performing linear regression to make predictions. At the core of our analysis is...

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Bibliographic Details
Main Authors: Agarwal, Anish, Amjad, Muhammad Jehangir, Shah, Devavrat, Shen, Dennis
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Association for Computing Machinery (ACM) 2021
Online Access:https://hdl.handle.net/1721.1/135068