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cff-version: 1.2.0
message: 'To cite package "rlppinv" in publications use:'
type: software
license: MIT
title: 'rlppinv: Linear Programming via Regularized Least Squares'
version: 2.0.0
doi: 10.32614/CRAN.package.rlppinv
abstract: 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.
authors:
- family-names: Bolotov
  given-names: Ilya
  email: ilya.bolotov@vse.cz
  orcid: https://orcid.org/0000-0003-1148-7144
repository: https://econcz.r-universe.dev
repository-code: https://github.com/econcz/rlppinv
commit: e9df78080757a8b3a8a00c4cc523e2a42b5005ce
url: https://github.com/econcz/rlppinv
date-released: '2026-06-07'
contact:
- family-names: Bolotov
  given-names: Ilya
  email: ilya.bolotov@vse.cz
  orcid: https://orcid.org/0000-0003-1148-7144