2 Scopus citations


Establishing an optimal sampling schedule is a crucial step toward a precise inference of the underlying functional mechanism of a process, especially when data collection is expensive/difficult. This work is concerned with optimal sampling plans for predicting a scalar response using a functional predictor when a quadratic regression relationship is present. An optimality criterion for selecting the best sampling schedules is derived, and some important properties of the criterion are provided. In addition, a bootstrap aggregating (bagging) strategy is proposed to enhance the quality of the obtained sampling schedule.

Original languageEnglish (US)
Article number91
JournalJournal of Statistical Theory and Practice
Issue number4
StatePublished - Dec 2021


  • Bagging
  • Functional data analysis
  • Functional principal component
  • Functional regression model

ASJC Scopus subject areas

  • Statistics and Probability


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