JICO: Joint and Individual Regression
Implements the JICO algorithm [Wang, P., Wang, H., Li, Q., Shen, D., & Liu, Y. (2022). <arXiv:2209.12388>], which solves the multi-group regression problem. The algorithm decomposes the responses from multiple groups into shared and group-specific
components, which are driven by low-rank approximations of joint and individual structures from the covariates respectively. It provides the implementation of
the algorithm so solve the iterative continuum regression problem with fixed rank selection, as well as the cross-validation function to perform hyperparameter tuning.
Please use the canonical form
to link to this page.