Hybrid exact-approximate design approach for sparse functional data. (English) Zbl 07771446
Summary: Optimal designs for sparse functional data under the functional empirical component (FEC) settings are studied. This design issue has some unique features, making it different from classical design problems. To efficiently obtain optimal exact and approximate designs, new computational methods and useful theoretical results are developed, and a hybrid exact-approximate design approach is proposed. The proposed methods are demonstrated to be efficient via simulation studies and a real example.
MSC:
| 62-08 | Computational methods for problems pertaining to statistics |
Keywords:
design efficiency; longitudinal data; mixed model equations; principal components; random effectsReferences:
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