Inference of High-dimensional Autoregressive Generalized Linear Models

9 May 2016Eric C. HallGarvesh RaskuttiRebecca Willett

Vector autoregressive models characterize a variety of time series in which linear combinations of current and past observations can be used to accurately predict future observations. For instance, each element of an observation vector could correspond to a different node in a network, and the parameters of an autoregressive model would correspond to the impact of the network structure on the time series evolution... (read more)

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