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AMS Weekly Seminar | Lecturer Francesco Sanna Passino
April 11 @ 1:30 pm - 2:30 pm
Location: Olin 305
When: April 11th at 1:30 p.m.
Title: Low-rank models for dynamic multiplex graphs and vector autoregressive processes
Abstract: This talk discusses low-rank models for two different types of data structures: dynamic multiplex graphs and panels of multivariate time series. The first part of the talk will present a doubly unfolded adjacency spectral embedding (DUASE) method for networks evolving over time, with different edge types, commonly known as multiplex networks. Statistical properties of DUASE will be discussed, and links with commonly used statistical models for clustering graphs will be presented. The second part of the talk will cover the case of a panel of multivariate time series where there is co-movement between the panel components, modelled via a vector autoregressive process. A Network Informed Restricted Vector Auto-Regressive (NIRVAR) process is proposed, with an algorithm that gives a low dimensional latent embedding of each component of the panel. Clustering in this latent space is then used to recover the non-zero entries of the VAR coefficient matrix. The proposed model outperforms alternative approaches in terms of prediction and inference in simulation studies and real-data examples in applications in finance and healthcare.
Zoom link: https://wse.zoom.us/j/94601022340