References in zbMATH (referenced in 32 articles )

Showing results 1 to 20 of 32.
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  1. Kolkiewicz, Adam; Rice, Gregory; Xie, Yijun: Projection pursuit based tests of normality with functional data (2021)
  2. Dai, Wenlin; Mrkvička, Tomáš; Sun, Ying; Genton, Marc G.: Functional outlier detection and taxonomy by sequential transformations (2020)
  3. Ieva, Francesca; Paganoni, Anna Maria: Component-wise outlier detection methods for robustifying multivariate functional samples (2020)
  4. Dai, Wenlin; Genton, Marc G.: Directional outlyingness for multivariate functional data (2019)
  5. Kosiorowski, Daniel; Rydlewski, Jerzy P.; Snarska, Małgorzata: Detecting a structural change in functional time series using local Wilcoxon statistic (2019)
  6. Martínez-Hernández, Israel; Genton, Marc G.; González-Farías, Graciela: Robust depth-based estimation of the functional autoregressive model (2019)
  7. Nagy, Stanislav; Ferraty, Frédéric: Data depth for measurable noisy random functions (2019)
  8. Shang, Han Lin: Dynamic principal component regression: application to age-specific mortality forecasting (2019)
  9. Shang, Han Lin; Yang, Yang; Kearney, Fearghal: Intraday forecasts of a volatility index: functional time series methods with dynamic updating (2019)
  10. Tian, Yahui; Gel, Yulia R.: Fusing data depth with complex networks: community detection with prior information (2019)
  11. Barrow, Devon; Kourentzes, Nikolaos: The impact of special days in call arrivals forecasting: a neural network approach to modelling special days (2018)
  12. Clara Happ: Object-Oriented Software for Functional Data (2017) arXiv
  13. Nanty, Simon; Helbert, Céline; Marrel, Amandine; Pérot, Nadia; Prieur, Clémentine: Uncertainty quantification for functional dependent random variables (2017)
  14. Serfling, Robert; Wijesuriya, Uditha: Depth-based nonparametric description of functional data, with emphasis on use of spatial depth (2017)
  15. Shang, Han Lin; Haberman, Steven: Grouped multivariate and functional time series forecasting: an application to annuity pricing (2017)
  16. Martin-Barragan, B.; Lillo, R. E.; Romo, J.: Functional boxplots based on epigraphs and hypographs (2016)
  17. Nanty, Simon; Helbert, Céline; Marrel, Amandine; Pérot, Nadia; Prieur, Clémentine: Sampling, metamodeling, and sensitivity analysis of numerical simulators with functional stochastic inputs (2016)
  18. Arribas-Gil, Ana; Romo, Juan: Discussion of “Multivariate functional outlier detection” (2015)
  19. Bali, Juan Lucas; Boente, Graciela: Influence function of projection-pursuit principal components for functional data (2015)
  20. Hubert, Mia; Rousseeuw, Peter J.; Segaert, Pieter: Multivariate functional outlier detection (2015)

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