Testing for stationarity of functional time series in the frequency domain
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Publication:2215748
DOI10.1214/19-AOS1895zbMath1455.62230arXiv1701.01741MaRDI QIDQ2215748
Publication date: 14 December 2020
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1701.01741
spectral analysislocally stationary processesfunctional data analysisfrequency domain methodsannual temperature curve
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional data analysis (62R10) Applications of statistics to environmental and related topics (62P12) Inference from stochastic processes and spectral analysis (62M15) Applications of statistics to physics (62P35)
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Cites Work
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- Fourier analysis of stationary time series in function space
- Functional data analysis with increasing number of projections
- Inference for functional data with applications
- Testing temporal constancy of the spectral structure of a time series
- Uniform convergence rates for nonparametric regression and principal component analysis in functional/longitudinal data
- Weakly dependent functional data
- On weak convergence of integral functionals of stochastic processes with applications to processes taking paths in \(L^ E_ p\)
- Fitting time series models to nonstationary processes
- Wavelet methods for continuous-time prediction using Hilbert-valued autoregressive processes
- Linear processes in function spaces. Theory and applications
- Locally stationary functional time series
- A note on Herglotz's theorem for time series on function spaces
- A test for second order stationarity of a multivariate time series
- A test for stationarity based on empirical processes
- Functional data analysis.
- Nonparametric functional data analysis. Theory and practice.
- Testing stationarity of functional time series
- Autoregressive Forecasting of Some Functional Climatic Variations
- A Wavelet-Based Test for Stationarity
- Structural breaks in time series
- A Spectral Domain Test for Stationarity of Spatio‐Temporal Data
- A Measure of Stationarity in Locally Stationary Processes With Applications to Testing
- A note on general quadratic forms of nonstationary stochastic processes
- Orthogonal Samples for Estimators in Time Series
- Detecting and Dating Structural Breaks in Functional Data Without Dimension Reduction
- A test for second-order stationarity of a time series based on the discrete Fourier transform
- Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
- On the Prediction of Stationary Functional Time Series
- Dynamic Functional Principal Components
- A Test for Stationarity for Irregularly Spaced Spatial Data
- On Properties of Functional Principal Components Analysis
