Variable selection and importance in presence of high collinearity: an application to the prediction of lean body mass from multi-frequency bioelectrical impedance

DOI10.1080/02664763.2020.1763930OpenAlexW3025063915MaRDI QIDQ5861598

Camillo Cammarota, Alessandro Pinto

Publication date: 1 March 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1763930

zbMATH Keywords

linear modelvariable selectionrandom forestsmulti-frequencyimportancebioimpedanceanthropometric variableslean body mass

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• R
• LambertW
• relaimpo
• rfPermute

Cites Work

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• A random forest guided tour
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• The elements of statistical learning. Data mining, inference, and prediction

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