freqdom.fda

R package freqdom.fda: Functional Time Series: Dynamic Functional Principal Components. Implementations of functional dynamic principle components analysis. Related graphic tools and frequency domain methods. These methods directly use multivariate dynamic principal components implementation, following the guidelines from Hormann, Kidzinski and Hallin (2016), Dynamic Functional Principal Component <doi:10.1111/rssb.12076>.


References in zbMATH (referenced in 26 articles , 1 standard article )

Showing results 1 to 20 of 26.
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  1. Bücher, Axel; Dette, Holger; Heinrichs, Florian: Detecting deviations from second-order stationarity in locally stationary functional time series (2020)
  2. Kokoszka, Piotr; Jouzdani, Neda Mohammadi: Frequency domain theory for functional time series: variance decomposition and an invariance principle (2020)
  3. Rubín, Tomáš; Panaretos, Victor M.: Sparsely observed functional time series: estimation and prediction (2020)
  4. Sang, Peijun; Cao, Jiguo: Functional single-index quantile regression models (2020)
  5. Shang, Han Lin: Dynamic principal component regression for forecasting functional time series in a group structure (2020)
  6. Shang, Han Lin: A comparison of Hurst exponent estimators in long-range dependent curve time series (2020)
  7. van Delft, Anne: A note on quadratic forms of stationary functional time series under mild conditions (2020)
  8. van Delft, Anne; Eichler, Michael: A note on Herglotz’s theorem for time series on function spaces (2020)
  9. Chen, Yichao; Pun, Chi Seng: A bootstrap-based KPSS test for functional time series (2019)
  10. Gao, Yuan; Shang, Han Lin; Yang, Yanrong: High-dimensional functional time series forecasting: an application to age-specific mortality rates (2019)
  11. Hashemi, Maryam; Zamani, Atefeh; Haghbin, Hossein: Rates of convergence of autocorrelation estimates for periodically correlated autoregressive Hilbertian processes (2019)
  12. Salish, Nazarii; Gleim, Alexander: A moment-based notion of time dependence for functional time series (2019)
  13. Hallin, Marc; Hörmann, Siegfried; Lippi, Marco: Optimal dimension reduction for high-dimensional and functional time series (2018)
  14. Hörmann, Siegfried; Kokoszka, Piotr; Nisol, Gilles: Testing for periodicity in functional time series (2018)
  15. Kokoszka, Piotr; Xiong, Qian: Extremes of projections of functional time series on data-driven basis systems (2018)
  16. Paparoditis, Efstathios: Sieve bootstrap for functional time series (2018)
  17. Shang, Han Lin: Bootstrap methods for stationary functional time series (2018)
  18. van Delft, Anne; Eichler, Michael: Locally stationary functional time series (2018)
  19. Cerovecki, Clément; Hörmann, Siegfried: On the CLT for discrete Fourier transforms of functional time series (2017)
  20. Berkes, István; Horváth, Lajos; Rice, Gregory: On the asymptotic normality of kernel estimators of the long run covariance of functional time series (2016)

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