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

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

Computational Statistics & Data Analysis, 2018, vol. 122, issue C, 101-114

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.

Keywords: Covariance function; Functional data analysis; Fetal growth; Longitudinal data; Prediction (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:122:y:2018:i:c:p:101-114

DOI: 10.1016/j.csda.2018.01.009

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