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In this work we introduce an algorithm designed for the imputation of missing functional data. The algorithm alternates between a curve imputation step and a parameter update step, resulting in an iterative procedure. The proposal is compared to well–known existing alternatives, showing outstanding results. Finally, we showcase the potential of the method using simulations and a real dataset.

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A New Algorithm for the Imputation of Missing Functional Data

  • 会议论文

  • 发表日期：

    2025年

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  • Marco Stefanucci

摘要

In this work we introduce an algorithm designed for the imputation of missing functional data. The algorithm alternates between a curve imputation step and a parameter update step, resulting in an iterative procedure. The proposal is compared to well–known existing alternatives, showing outstanding results. Finally, we showcase the potential of the method using simulations and a real dataset.