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Studies involving functional data frequently require curve registration, i.e. the alignment of salient features in the temporal domain, as a preliminary step before the application of inferential techniques. Through this procedure, phase variability becomes negligible, thus allowing to focus solely on amplitude variability. This work introduces a Bayesian model for curve alignment and applies it to a biomechanical dataset with three groups of patients.

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Bayesian Models for Registration of Functional Data

  • 会议论文

  • 发表日期：

    2025年

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  • Jacopo Gardella,
  • Rossella Carone,
  • Simone Ciardulli,
  • Nicola Francescon,
  • Matteo Freddi,
  • Elisa Garlanda,
  • Alessandro Casa,
  • Alessia Pini

摘要

Studies involving functional data frequently require curve registration, i.e. the alignment of salient features in the temporal domain, as a preliminary step before the application of inferential techniques. Through this procedure, phase variability becomes negligible, thus allowing to focus solely on amplitude variability. This work introduces a Bayesian model for curve alignment and applies it to a biomechanical dataset with three groups of patients.