Introduced more than a half-century ago, Granger causality has become a popular tool for
analyzing time series data in many application domains, from economics and finance to …

At present, rotating machinery is widely used in all walks of life and has become the key
equipment in many production processes. It is of great significance to strengthen the …

Vector autoregression (VAR) is a fundamental tool for modeling multivariate time series.
However, as the number of component series is increased, the VAR model becomes …

The classical vector autoregressive model is a fundamental tool for multivariate time series
analysis. However, it involves too many parameters when the number of time series and lag …

Individuals or companies in a large social or financial network often display rather
heterogeneous behaviors for various reasons. In this work, we propose a network vector …

We develop an LM test for Granger causality in high-dimensional (HD) vector autoregressive
(VAR) models based on penalized least squares estimations. To obtain a test retaining the …

Modeling responses on the nodes of a large-scale network is an important task that arises
commonly in practice. This paper proposes a community network vector autoregressive …

Recently, the price of a stock market changes often owing to a variety of factors. As a result,
making an accurate stock price prediction is a difficult process. Hence, this research work …

We propose FNETS, a methodology for network estimation and forecasting of high-
dimensional time series exhibiting strong serial-and cross-sectional correlations. We …

We consider the problem of estimating a linear time-invariant (LTI) dynamical system from a
single trajectory via streaming algorithms, which is encountered in several applications …