Vector autoregressive (VAR) modelling is one of the most popular approaches in multivariate time series analysis. The parameters interpretation is simple, and provide an intuitive...
Geometry compression is an effective way to distribute high-volume geometry data within limited bandwidth and storage capacity. In this paper, a new time-varying 3D geometry compre...
: We propose a wavelet multiscale decomposition based autoregressive approach for the prediction of one-hour ahead ahead load based on historical electricity load data. This approa...
D. Benaouda, Fionn Murtagh, Jean-Luc Starck, O. Re...
This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first ...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...