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http://repositorio.ufla.br/jspui/handle/1/40647
Título: | Explaining the generalized cross-validation on linear models |
Palavras-chave: | Circulant Matrices PRESS Statistics Prediction Error Validação cruzada Modelos lineares Matrizes Circulantes Estatística PRESS Erro de previsão |
Data do documento: | 2019 |
Editor: | Science Publications |
Citação: | CHAVES, L. M. et al. Explaining the generalized cross-validation on linear models. Journal of Mathematics and Statistics, Dubai, v. 15, p. 298-307, 2019. |
Resumo: | 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. |
URI: | http://repositorio.ufla.br/jspui/handle/1/40647 |
Aparece nas coleções: | DEX - Artigos publicados em periódicos |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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ARTIGO_Explaining the Generalized Cross-Validation on Linear Models.pdf | 1,17 MB | Adobe PDF | Visualizar/Abrir |
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