Sparse Regression for Related Problems
Calculate deviance
Regression Coefficients
Construct penalty factors
Construct internal and external weights
Metrics for sign detection
Model comparison
Data fusion
Extract dimensionality.
Link function
logit function
Create folds for multi-task and transfer learning
Mean function
Available methods
Pairwise differences
Visualise metric that depends on two parameters
Out-of-sample Predictions
Print sparselink object
Sigmoid function
Data simulation for related problems
Sparse regression for related problems
Sparse regression for related problems
Train and test model
Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings, as proposed by Rauschenberger et al. (2025) <https://orbilu.uni.lu/handle/10993/63425>.
Useful links