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On Applying Optimal Design of Experiments when Functional Observations Occur

  • Giacomo AlettiEmail author
  • Caterina May
  • Chiara Tommasi
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

In this work we study the theory of optimal design of experiments when functional observations occur. We provide the best estimate for the functional coefficient in a linear model with functional response and multivariate predictor, exploiting fully the information provided by both functions and derivatives. We define different optimality criteria for the estimate of a functional coefficient. Then, we provide a strong theoretical foundation to prove that the computation of these optimal designs, in the case of linear models, is the same as in the classical theory, but a different interpretation needs to be given.

Keywords

Optimal Design Functional Response Functional Data Analysis Good Linear Unbiased Estimator Continuous Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Università degli Studi di MilanoMilanoItaly
  2. 2.University of Eastern PiedmontNovaraItaly

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