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Editorial on the special issue on Functional Data Analysis and Related Topics

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  • Germán Aneiros

    (Universidade da Coruña
    ITMATI)

  • Ricardo Cao

    (Universidade da Coruña
    ITMATI)

  • Philippe Vieu

    (Université Paul Sabatier)

Abstract

No abstract is available for this item.

Suggested Citation

  • Germán Aneiros & Ricardo Cao & Philippe Vieu, 2019. "Editorial on the special issue on Functional Data Analysis and Related Topics," Computational Statistics, Springer, vol. 34(2), pages 447-450, June.
    • Handle: RePEc:spr:compst:v:34:y:2019:i:2:d:10.1007_s00180-019-00892-0
    DOI: 10.1007/s00180-019-00892-0
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    References listed on IDEAS

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    1. Adriano Zanin Zambom & Julian A. A. Collazos & Ronaldo Dias, 2019. "Functional data clustering via hypothesis testing k-means," Computational Statistics, Springer, vol. 34(2), pages 527-549, June.
    2. Jan Koláček & Ondřej Pokora & Daniela Kuruczová & Tzai-Wen Chiu, 2019. "Benefits of functional PCA in the analysis of single-trial auditory evoked potentials," Computational Statistics, Springer, vol. 34(2), pages 617-629, June.
    3. Ping Yu & Zhongyi Zhu & Zhongzhan Zhang, 2019. "Robust exponential squared loss-based estimation in semi-functional linear regression models," Computational Statistics, Springer, vol. 34(2), pages 503-525, June.
    4. O. I. Traore & P. Cristini & N. Favretto-Cristini & L. Pantera & P. Vieu & S. Viguier-Pla, 2019. "Clustering acoustic emission signals by mixing two stages dimension reduction and nonparametric approaches," Computational Statistics, Springer, vol. 34(2), pages 631-652, June.
    5. Tomasz Górecki & Łukasz Smaga, 2019. "fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data," Computational Statistics, Springer, vol. 34(2), pages 571-597, June.
    6. Gianluca Sottile & Giada Adelfio, 2019. "Clusters of effects curves in quantile regression models," Computational Statistics, Springer, vol. 34(2), pages 551-569, June.
    7. Shin-ichi Tsukada, 2019. "High dimensional two-sample test based on the inter-point distance," Computational Statistics, Springer, vol. 34(2), pages 599-615, June.
    8. Mariano Valderrama, 2007. "An overview to modelling functional data," Computational Statistics, Springer, vol. 22(3), pages 331-334, September.
    9. Manuel Febrero-Bande & Wenceslao González-Manteiga & Manuel Oviedo de la Fuente, 2019. "Variable selection in functional additive regression models," Computational Statistics, Springer, vol. 34(2), pages 469-487, June.
    10. Enea G. Bongiorno & Aldo Goia & Philippe Vieu, 2019. "Modeling functional data: a test procedure," Computational Statistics, Springer, vol. 34(2), pages 451-468, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Bongiorno, E.G. & Goia, A. & Vieu, P., 2020. "Estimating the complexity index of functional data: Some asymptotics," Statistics & Probability Letters, Elsevier, vol. 161(C).
    2. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    3. Helander, Sami & Laketa, Petra & Ilmonen, Pauliina & Nagy, Stanislav & Van Bever, Germain & Viitasaari, Lauri, 2022. "Integrated shape-sensitive functional metrics," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    4. Mohammedi, Mustapha & Bouzebda, Salim & Laksaci, Ali, 2021. "The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data," Journal of Multivariate Analysis, Elsevier, vol. 181(C).
    5. Aneiros, Germán & Novo, Silvia & Vieu, Philippe, 2022. "Variable selection in functional regression models: A review," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    6. Aneiros, Germán & Horová, Ivana & Hušková, Marie & Vieu, Philippe, 2022. "On functional data analysis and related topics," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    7. Aubin, Jean-Baptiste & Bongiorno, Enea G. & Goia, Aldo, 2022. "The correction term in a small-ball probability factorization for random curves," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    8. Ali Laksaci & Elias Ould Saïd & Mustapha Rachdi, 2021. "Uniform consistency in number of neighbors of the kNN estimator of the conditional quantile model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(6), pages 895-911, August.
    9. Ibrahim M. Almanjahie & Zoulikha Kaid & Ali Laksaci & Mustapha Rachdi, 2022. "Estimating the Conditional Density in Scalar-On-Function Regression Structure: k -N-N Local Linear Approach," Mathematics, MDPI, vol. 10(6), pages 1-16, March.
    10. Amel, Azzi & Ali, Laksaci & Elias, Ould Saïd, 2022. "On the robustification of the kernel estimator of the functional modal regression," Statistics & Probability Letters, Elsevier, vol. 181(C).
    11. Novo, Silvia & Aneiros, Germán & Vieu, Philippe, 2021. "A kNN procedure in semiparametric functional data analysis," Statistics & Probability Letters, Elsevier, vol. 171(C).
    12. Zdeněk Hlávka & Marie Hušková & Simos G. Meintanis, 2021. "Testing serial independence with functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 603-629, September.
    13. Mustapha Rachdi & Ali Laksaci & Zoulikha Kaid & Abbassia Benchiha & Fahimah A. Al‐Awadhi, 2021. "k‐Nearest neighbors local linear regression for functional and missing data at random," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(1), pages 42-65, February.
    14. Roy, Arkaprava & Ghosal, Subhashis, 2022. "Optimal Bayesian smoothing of functional observations over a large graph," Journal of Multivariate Analysis, Elsevier, vol. 189(C).

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