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Functional Data Analysis in Designed Experiments

  • Bairu ZhangEmail author
  • Heiko Großmann
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

F-type tests for functional ANOVA models implicitly assume that the response curves are generated by a completely randomized design. By using the split-plot design as an example it is illustrated how these tests can be extended to more complex ANOVA models. In order to derive the test statistics and their approximate null distributions, Hasse diagrams for representing the structure of the experiment are combined with a stochastic process perspective. The application of the more general F-type tests is illustrated for simulated data.

Keywords

Covariance Function Functional Data Null Distribution Treatment Factor Hasse Diagram 
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.Queen Mary University of LondonLondonUK
  2. 2.Otto-von-Guericke-University MagdeburgMagdeburgGermany

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