Identifying the spectral representation of Hilbertian time series

DOI10.1016/J.SPL.2016.06.014zbMath1348.60029arXiv1604.02702OpenAlexW2963156586MaRDI QIDQ312080

Eduardo Horta, Flávio Augusto Ziegelmann

Publication date: 13 September 2016

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1604.02702

zbMATH Keywords

estimationdimension reductionspectral representationcovariance operatorfunctional principal component analysis\(\sqrt{n}\)-consistencyHilbertian time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Stationary stochastic processes (60G10)

Related Items (3)

Mixing conditions of conjugate processes ⋮ Conjugate processes: theory and application to risk forecasting ⋮ Wavelet estimation of the dimensionality of curve time series

Cites Work

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• Identifying the finite dimensionality of curve time series
• Basic properties of strong mixing conditions. A survey and some open questions
• Linear processes in function spaces. Theory and applications
• Assessing the Finite Dimensionality of Functional Data

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