STATISTICS SEMINAR SERIES
Friday, October 3, 4:10pm, MSB 1147 (Colloquium Room) Refreshments at 3:30pm in MSB 4110 (Statistics Lounge)
Speaker: Qiwei Yao (London School of Economics, UK)
Title: “Segmenting Multiple Time Series by Contemporaneous Linear Transformation”
Abstract: We seek for a contemporaneous linear transformation for a $p$-variate time series such that the transformed series is segmented into several lower-dimensional subseries, and those subseries are uncorrelated with each other both contemporaneously and serially. The method boils down to an eigenanalysis and, if $p$ is large, a permutation in terms of maximum cross-correlations or FDR based on multiple tests. The asymptotic theory is established for both fixed $p$ and diverging $p$ when the sample size $n$ goes to infinity, reflecting the fact that the method also applies when the dimension $p$ is large in relation to $n$. Numerical experiments with both simulated and real datasets indicate that the proposed method is an effective initial step in analysing multiple time series data, which leads to substantial dimension-reduction in modelling and forecasting high-dimensional linear dynamical structures.