On consistency and sparsity for high-dimensional functional time series with application to autoregressions

Publication date: 19 December 2022

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2003.11462

zbMATH Keywords

sparsity functional principal component analysis high-dimensional functional time series functional stability measure non-asymptotics vector functional autoregression

Mathematics Subject Classification ID

Inference from stochastic processes (62Mxx) Multivariate analysis (62Hxx) Nonparametric inference (62Gxx)

Related Items (3)

White noise testing for functional time series ⋮ An autocovariance-based learning framework for high-dimensional functional time series ⋮ On consistency and sparsity for high-dimensional functional time series with application to autoregressions

Uses Software

fda (R)

Cites Work

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