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Journal Articles Electronic Journal of Linear Algebra Year : 2019

An Eigenvalue Approach For Estimating The Generalized Cross Validation Function For Correlated Matrices

Christos Koukouvinos
  • Function : Author
Marilena Mitrouli
  • Function : Author
Ondrej Turek
  • Function : Author

Abstract

This work proposes a fast estimate for the generalized cross-validation function when the design matrix of an experiment has correlated columns. The eigenvalue structure of this matrix is used to derive probability bounds satisfied by an appropriate index of proximity, which provides a simple and accurate estimate for the numerator of the generalized cross-validation function. The denominator of the function is evaluated by an analytical formula. Several simulation tests performed in statistical models having correlated design matrix with intercept confirm the reliability of the proposed probabilistic bounds and indicate the applicability of the proposed estimate for these models.

Dates and versions

hal-04413543 , version 1 (23-01-2024)

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Christos Koukouvinos, Khalide Jbilou, Marilena Mitrouli, Ondrej Turek. An Eigenvalue Approach For Estimating The Generalized Cross Validation Function For Correlated Matrices. Electronic Journal of Linear Algebra, 2019, 35, pp.482-496. ⟨10.13001/1081-3810.4090⟩. ⟨hal-04413543⟩
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