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A novel two-way functional linear model with applications in human mortality data analysis

Author

Listed:
  • Xingyu Yan
  • Jiaqian Yu
  • Weiyong Ding
  • Hao Wang
  • Peng Zhao

Abstract

Recently, two-way or longitudinal functional data analysis has attracted much attention in many fields. However, little is known on how to appropriately characterize the association between two-way functional predictor and scalar response. Motivated by a mortality study, in this paper, we propose a novel two-way functional linear model, where the response is a scalar and functional predictor is two-way trajectory. The model is intuitive, interpretable and naturally captures relationship between each way of two-way functional predictor and scalar-type response. Further, we develop a new estimation method to estimate the regression functions in the framework of weak separability. The main technical tools for the construction of the regression functions are product functional principal component analysis and iterative least square procedure. The solid performance of our method is demonstrated in extensive simulation studies. We also analyze the mortality dataset to illustrate the usefulness of the proposed procedure.

Suggested Citation

  • Xingyu Yan & Jiaqian Yu & Weiyong Ding & Hao Wang & Peng Zhao, 2024. "A novel two-way functional linear model with applications in human mortality data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 51(10), pages 2025-2038, July.
    • Handle: RePEc:taf:japsta:v:51:y:2024:i:10:p:2025-2038
    DOI: 10.1080/02664763.2023.2253379
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