Develops consistent estimators for pre- and post-change factor loadings and change-point location in high-dimensional time series allowing strong cross-sectional noise dependence through self-normalized testing.
Sparse vector autoregressive modeling,
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Factor Analysis for High-Dimensional Time Series with Change Point
Develops consistent estimators for pre- and post-change factor loadings and change-point location in high-dimensional time series allowing strong cross-sectional noise dependence through self-normalized testing.