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Ordinal classification of 3D brain structures by functional data analysis

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  • Ferrando, L.
  • Epifanio, I.
  • Ventura-Campos, N.

Abstract

We introduce several ordinal classification methods for functional data, specifically multiargument and multivariate functional data. Their performance is analyzed in four real data sets that belong to a neuroeducational problem and a neuropathological problem.

Suggested Citation

  • Ferrando, L. & Epifanio, I. & Ventura-Campos, N., 2021. "Ordinal classification of 3D brain structures by functional data analysis," Statistics & Probability Letters, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:stapro:v:179:y:2021:i:c:s0167715221001899
    DOI: 10.1016/j.spl.2021.109227
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    References listed on IDEAS

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    1. Amelia Simó & M. Victoria Ibáñez & Irene Epifanio & Vicent Gimeno, 2020. "Generalized partially linear models on Riemannian manifolds," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 641-661, June.
    2. Bo Wang & Jian Qing Shi, 2014. "Generalized Gaussian Process Regression Model for Non-Gaussian Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1123-1133, September.
    3. Yao, Fang & Muller, Hans-Georg & Wang, Jane-Ling, 2005. "Functional Data Analysis for Sparse Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 577-590, June.
    4. Jafer Rahman & Shihua Luo & Yawen Fan & Xiaohui Liu, 2020. "Semiparametric efficient inferences for generalised partially linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 32(3), pages 704-724, July.
    5. Epifanio, Irene & Ventura-Campos, Noelia, 2011. "Functional data analysis in shape analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2758-2773, September.
    Full references (including those not matched with items on IDEAS)

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