An implementation of both the equality and inequality constrained lasso functions for the algorithm described in "Penalized and Constrained Optimization" by James, Paulson, and Rusmevichientong (Journal of the American Statistical Association, 2019; see <http://wwwbcf.usc.edu/~gareth/research/PAC.pdf> for a fulltext version of the paper). The algorithm here is designed to allow users to define linear constraints (either equality or inequality constraints) and use a penalized regression approach to solve the constrained problem. The functions here are used specifically for constraints with the lasso formulation, but the method described in the PaC paper can be used for a variety of scenarios. In addition to the simple examples included here with the corresponding functions, complete code to entirely reproduce the results of the paper is available online through the Journal of the American Statistical Association.
Package details 


Author  Courtney Paulson [aut, cre], Gareth James [ctb], Paat Rusmevichientong [ctb] 
Maintainer  Courtney Paulson <cpaulson@rhsmith.umd.edu> 
License  GPL3 
Version  1.0.0 
URL  http://wwwbcf.usc.edu/~gareth/research/PAC.pdf 
Package repository  View on CRAN 
Installation 
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