Package: fusedTree 1.1.0

fusedTree: Fused Partitioned Regression for Clinical and Omics Data

Fit (generalized) linear regression models in each leaf node of a tree. The tree is constructed using clinical variables only. The linear regression models are constructed using (high-dimensional) omics variables only. The leaf-node-specific regression models are estimated using the penalized likelihood including a standard ridge (L2) penalty and a fusion penalty that links the leaf-node-specific regression models to one another. The intercepts of the leaf nodes reflect the effects of the clinical variables and are left unpenalized. The tree, fitted with the clinical variables only, should be constructed outside of the package with the 'rpart' 'R' package. See Goedhart and others (2024) <doi:10.48550/arXiv.2411.02396> for details on the method.

Authors:Jeroen M. Goedhart [aut, cre, cph], Wessel N. van Wieringen [aut], Thomas Klausch [ths], Mark A. van de Wiel [ths], Hanarth Fonds [fnd]