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A joint design for functional data with application to scheduling ultrasound scans

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  • Park, So Young
  • Xiao, Luo
  • Willbur, Jayson D.
  • Staicu, Ana-Maria
  • Jumbe, N. L’ntshotsholé

Abstract

A joint design for sampling functional data is proposed to achieve optimal prediction of both functional data and a scalar outcome. The motivating application is fetal growth, where the objective is to determine the optimal times to collect ultrasound measurements in order to recover fetal growth trajectories and to predict child birth outcomes. The joint design is formulated using an optimization criterion and implemented in a pilot study. Performance of the proposed design is evaluated via simulation study and application to fetal ultrasound data.

Suggested Citation

  • Park, So Young & Xiao, Luo & Willbur, Jayson D. & Staicu, Ana-Maria & Jumbe, N. L’ntshotsholé, 2018. "A joint design for functional data with application to scheduling ultrasound scans," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 101-114.
    • Handle: RePEc:eee:csdana:v:122:y:2018:i:c:p:101-114
    DOI: 10.1016/j.csda.2018.01.009
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    References listed on IDEAS

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    Cited by:

    1. Craig, Sarah J.C. & Kenney, Ana M. & Lin, Junli & Paul, Ian M. & Birch, Leann L. & Savage, Jennifer S. & Marini, Michele E. & Chiaromonte, Francesca & Reimherr, Matthew L. & Makova, Kateryna D., 2023. "Constructing a polygenic risk score for childhood obesity using functional data analysis," Econometrics and Statistics, Elsevier, vol. 25(C), pages 66-86.
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    3. Rha, Hyungmin & Kao, Ming-Hung & Pan, Rong, 2020. "Design optimal sampling plans for functional regression models," Computational Statistics & Data Analysis, Elsevier, vol. 146(C).

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