Fused Lasso for High-Dimensional Regression over Groups
Big eigenvalue calculation
Optimise the fused L2 model with glmnet (using transformed input data)
Fused lasso optimisation with proximal-gradient method. (Chen et al. 2...
Following a call to fusedLassoProximal, returns the actual number of i...
Generate block diagonal matrices to allow for fused L2 optimization wi...
Enables high-dimensional penalized regression across heterogeneous subgroups. Fusion penalties are used to share information about the linear parameters across subgroups. The underlying model is described in detail in Dondelinger and Mukherjee (2017) <arXiv:1611.00953>.