CLSP: Stata module providing Convex Least Squares Programming (CLSP) is a modular two-step estimator for solving underdetermined, ill-posed, or structurally constrained least-squares problems

Ilya Bolotov ()
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Ilya Bolotov: Prague University of Economics and Business

Statistical Software Components from Boston College Department of Economics

Abstract: Convex Least Squares Programming (CLSP) is a modular two-step estimator for solving underdetermined, ill-posed, or structurally constrained least-squares problems. It combines pseudoinverse-based estimation with convex-programming correction methods inspired by Lasso, Ridge, and Elastic Net to ensure numerical stability, constraint enforcement, and interpretability. The package also provides numerical stability analysis and CLSP-specific diagnostics, including partial R^2, normalized RMSE (NRMSE), Monte Carlo t-tests for mean NRMSE, and condition-number-based confidence bands.

Language: Stata
Requires: Stata version 16 and Python modules pyclsp, numpy, cvxpy
Keywords: linear programming; least squares; pseudoinverse; singular value decomposition (search for similar items in EconPapers)
Date: 2026-01-20
Note: This module should be installed from within Stata by typing "ssc install clsp". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/c/clsp.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/clsp.sthlp help file (text/plain)

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