Thresholding Approach for Low-Rank Correlation Matrix Based on MM Algorithm

Background: Low-rank approximation is used to interpret the features of a correlation matrix using visualization tools; however, a low-rank approximation may result in an estimation that is far from zero, even if the corresponding original value is zero. In such a case, the results lead to a misinte...

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Detalles Bibliográficos
Autores principales: Tanioka, Kensuke, Furotani, Yuki, Hiwa, Satoru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141820/
https://www.ncbi.nlm.nih.gov/pubmed/35626464
http://dx.doi.org/10.3390/e24050579

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141820/
https://www.ncbi.nlm.nih.gov/pubmed/35626464
http://dx.doi.org/10.3390/e24050579

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