Functions for computing split regularized estimators defined in Christidis, Lakshmanan, Smucler and Zamar (2019) <arXiv:1712.03561>. The approach fits linear regression models that split the set of covariates into groups. The optimal split of the variables into groups and the regularized estimation of the regression coefficients are performed by minimizing an objective function that encourages sparsity within each group and diversity among them. The estimated coefficients are then pooled together to form the final fit.
|Author||Anthony Christidis <email@example.com>, Ezequiel Smucler <firstname.lastname@example.org>, Ruben Zamar <email@example.com>|
|Maintainer||Anthony Christidis <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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