Event Date
Speaker: Qiwei Yao (Professor, Statistics, London School of Economics)
Title: "Modelling Matrix Time Series via a Tensor CP-Decomposition"
Abstract : We consider modelling matrix time series based on a tensor CP-decomposition. Instead of using the alternative least squares algorithm which is the standard practice for estimating CP-decompositions, we propose a new and one-pass estimation procedure based on a generalized eigenanalysis constructed from the serial dependence structure of the underlying process. To overcome the intricacy of solving a rank-reduced generalized eigenequation, we propose a further refined approach which projects it into a lower-dimensional full-ranked eigenequation. This refined method significantly improves the finite-sample performance of the estimation. The asymptotic theory has been established under a general setting without the stationarity. It shows, for example, that all the component coefficient vectors in the CP-decomposition are estimated consistently with certain convergence rates. The proposed model and the estimation method are also illustrated with both simulated and real data, showing effective dimension-reduction in modelling and forecasting matrix time series.
Faculty web page (links to LSE): https://stats.lse.ac.uk/q.yao/
Seminar Date/Time: Thursday May 23, 2024, at 2:10pm
Location: MSB 1147 (Refreshments 3:30pm)