Kavli Affiliate: Feng Long| Summary: We propose a unified ridge-regularized Hotelling framework for detecting and locating mean changes in functional time series. A growing basis expansion converts the functional observations into high-dimensional score vectors. Their long-run covariance is estimated by an edge-corrected difference-based procedure. Ridge regularization stabilizes inference under spectral decay. An explicit local-power formula […]
Continue.. Adaptive Ridge-Regularized Hotelling Change-Point Tests for Functional Data