rlppinv
Linear Programming via Regularized Least Squares
The Linear Programming via Regularized Least Squares (LPPinv) is a two-stage estimation method that reformulates linear programs as structured least-squares problems. Based on the Convex Least Squares Programming (CLSP) framework, LPPinv solves linear inequality, equality, and bound constraints by (1) constructing a canonical constraint system and computing a pseudoinverse projection, followed by (2) a convex-programming correction stage to refine the solution under additional regularization (e.g., Lasso, Ridge, or Elastic Net). LPPinv is intended for underdetermined and ill-posed linear problems, for which standard solvers fail.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.0 |
rolling linux/jammy R-4.5 | rlppinv_0.3.0.tar.gz |
19.9 KiB |
0.3.0 |
rolling linux/noble R-4.5 | rlppinv_0.3.0.tar.gz |
19.8 KiB |
0.3.0 |
rolling source/ R- | rlppinv_0.3.0.tar.gz |
5.6 KiB |
0.3.0 |
latest linux/jammy R-4.5 | rlppinv_0.3.0.tar.gz |
19.9 KiB |
0.3.0 |
latest linux/noble R-4.5 | rlppinv_0.3.0.tar.gz |
19.8 KiB |
0.3.0 |
latest source/ R- | rlppinv_0.3.0.tar.gz |
5.6 KiB |
0.3.0 |
2026-04-26 source/ R- | rlppinv_0.3.0.tar.gz |
5.6 KiB |
0.3.0 |
2026-04-23 source/ R- | rlppinv_0.3.0.tar.gz |
5.6 KiB |
0.3.0 |
2026-04-09 windows/windows R-4.5 | rlppinv_0.3.0.zip |
22.7 KiB |