An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series

arXiv:2209.01172v4 Announce Type: replace-cross
Abstract: As a special infinite-order vector autoregressive (VAR) model, the vector autoregressive moving average (VARMA) model can capture much richer temporal patterns than the widely used finite-order VAR model. However, its practicality has long been hindered by its non-identifiability, computational intractability, and difficulty of interpretation, especially for high-dimensional time series. This paper proposes a novel sparse infinite-order VAR model for high-dimensional time series, which avoids all above drawbacks while inheriting essential temporal patterns of the VARMA …

abstract arxiv autoregressive model computational moving patterns series stat.me stat.ml temporal time series type vector