Generalized Network Autoregressive Processes and the GNAR Package
Abstract
This article introduces the GNAR package, which fits, predicts, and simulates from a powerful new class of generalized network autoregressive processes. Such processes consist of a multivariate time series along with a real, or inferred, network that provides information about inter-variable relationships. The GNAR model relates values of a time series for a given variable and time to earlier values of the same variable and of neighboring...
Paper Details
Title
Generalized Network Autoregressive Processes and the GNAR Package
Published Date
Jan 1, 2020
Volume
96
Issue
5
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