The Markov property is widely imposed in analysis of time series data.
C...
Analysis of networks that evolve dynamically requires the joint modellin...
We propose a new estimation method for the spatial blind source separati...
We propose to model matrix time series based on a tensor CP-decompositio...
A standing challenge in data privacy is the trade-off between the level ...
We propose a contemporaneous bilinear transformation for matrix time ser...
We propose a new unsupervised learning method for clustering a large num...
We propose a first-order autoregressive model for dynamic network proces...
Probabilistic forecasting of electricity load curves is of fundamental
i...
We propose a new unit-root test for a stationary null hypothesis H_0
aga...
High-dimensional multivariate spatial-temporal data arise frequently in ...
Testing for white noise is a classical yet important problem in statisti...
While it is common practice in applied network analysis to report variou...
We propose a new class of spatio-temporal models with unknown and banded...