semvec/pypi-packages huggingface dataset:
pysmme 1.0
Soft maximin estimation in Python
License: mit
Requires Python: >=3.6

Efficient C++ procedure for solving the Lasso or SCAD penalized soft maximin problem. 

This is a C++ implementation of two proximal
gradient based algorithms (NPG and FISTA) that solve different forms of the soft
maximin problem from Lund et al., 2022 see https://doi.org/10.1111/sjos.12580. 
1) For general group specific design the soft maximin problem is solved using 
the NPG algorithm.
2) For fixed identical design across groups, the  soft maximin problem is solved using  
either the FISTA algorithm or the NPG algorithm in the following two cases:
i) For a tensor structured design matrix the algorithms use array arithmetic  to 
avoid the design matrix and speed computations ii) For a wavelet based design 
matrix the algorithms use the pyramid algorithm to avoid the design matrix and speed up
computations. Multi-threading is possible when openMP is available.