TY  - JOUR
AU  - Chaves, Lucas Monteiro 
AU  - Carvalho, Laerte Dias de 
AU  - Reis, Carlos José dos 
AU  - Souza, Devanil Jaques de 
PY  - 2019
TI  - Explaining the Generalized Cross-Validation on Linear Models
JF  - Journal of Mathematics and Statistics
VL  - 15
IS  - 1
DO  - 10.3844/jmssp.2019.298.307
UR  - https://thescipub.com/abstract/jmssp.2019.298.307
AB  - 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.