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A function \(f(\textbf{x})\) , assumed depending on D random variables, \(x_1, \dots , x_D\) , can be decomposed as [1] that, with the property of with \(\mathbb E_i\) the expectation with respect to any coordinate i in the set \((i_1, \dots , i_d)\) , \(1 \le d \le D\) , results in the orthogonality of functions involved in the previous decomposition.

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Analysis of Variance, ANOVA

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Francisco Chinesta,
  • Elías Cueto,
  • Victor Champaney,
  • Chady Ghnatios,
  • Amine Ammar,
  • Nicolas Hascoët,
  • David González,
  • Icíar Alfaro,
  • Daniele Di Lorenzo,
  • Angelo Pasquale,
  • Dominique Baillargeat

摘要

A function \(f(\textbf{x})\) , assumed depending on D random variables, \(x_1, \dots , x_D\) , can be decomposed as [1] that, with the property of with \(\mathbb E_i\) the expectation with respect to any coordinate i in the set \((i_1, \dots , i_d)\) , \(1 \le d \le D\) , results in the orthogonality of functions involved in the previous decomposition.