@article {10.3844/jmssp.2019.298.307,
article_type = {journal},
title = {Explaining the Generalized Cross-Validation on Linear Models},
author = {Chaves, Lucas Monteiro and Carvalho, Laerte Dias de and Reis, Carlos José dos and Souza, Devanil Jaques de},
volume = {15},
year = {2019},
month = {Oct},
pages = {298-307},
doi = {10.3844/jmssp.2019.298.307},
url = {https://thescipub.com/abstract/jmssp.2019.298.307},
abstract = {Cross-Validation is a model validation method widely used by the scientific community. The Generalized Cross-Validation (GCV) is an invariant version of the usual Cross-Validation method. This generalization was obtained using the non usual theory of circulant complex matrices. In this work we intend to give a clear and complete exposition concerning the linear algebra assumptions required by the theory. The aim was to make this text accessible to a wide audience of statisticians and non-statisticians who use the Cross-Validation method in their research activities. It is also intended to supply the absence of a basic reference on this topic in the literature.},
journal = {Journal of Mathematics and Statistics},
publisher = {Science Publications}
}