Optimal data acquisition for sparse functional data analysis

One of the crucial steps in most scientific studies is acquiring high-quality data to ensure precise and valid inference. This necessitates a well-structured data collection plan, for which research on optimal designs offers valuable tools and guidance. In this bridge-to-research talk, some classical optimal design approaches for collecting informative data for regression analysis will first be introduced. New challenges and research findings concerning the design of studies involving sparse functional data analysis (FDA) will then be presented. As a significant advancement in data analysis methods, sparse FDA has gained popularity and proven powerful in extracting useful information from functional data observed at sparse, and possibly irregularly spaced, time points. However, research on optimal designs for sparse FDA is currently underdeveloped. Our research contributes to this field by offering some guidance on optimizing the use of limited resources to efficiently collect the most informative data.

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