Develops AutoHSIC, a kernel-based lagged U-statistic for serial independence testing in stationary time series, with limiting distributions under null and alternatives plus asymptotically valid wild bootstrap.
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2 Pith papers cite this work. Polarity classification is still indexing.
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MoFI-FLR recovers active covariates and identifies their true functional forms (simple or complex) in high-dimensional functional linear regressions.
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Testing for Serial Independence via Auto Hilbert-Schmidt Independence Criterion
Develops AutoHSIC, a kernel-based lagged U-statistic for serial independence testing in stationary time series, with limiting distributions under null and alternatives plus asymptotically valid wild bootstrap.
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Model Form Identification in High-Dimensional Functional Linear Regressions
MoFI-FLR recovers active covariates and identifies their true functional forms (simple or complex) in high-dimensional functional linear regressions.