Bayesian wavelet-packet historical functional linear models

@article{Meyer2021BayesianWH,
  title={Bayesian wavelet-packet historical functional linear models},
  author={Mark J Meyer and Elizabeth J. Malloy and B. Coull},
  journal={Stat. Comput.},
  year={2021},
  volume={31},
  pages={14}
}
Historical Functional Linear Models (HFLM) quantify associations between a functional predictor and functional outcome where the predictor is an exposure variable that occurs before, or at least concurrently with, the outcome. Current work on the HFLM is largely limited to frequentist estimation techniques that employ spline-based basis representations. In this work, we propose a novel use of the discrete wavelet-packet transformation, which has not previously been used in functional models, to… 

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