A closed form solution for tre least squares regression problem with linear inequality constraints
- 1 January 1984
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 13 (9) , 1127-1134
- https://doi.org/10.1080/03610928408828746
Abstract
In this paper we consider a linear model Y = Xβ+e with linear inequality constraints R'β≥r, where X and R are known and full column rank matrices. The closed form of the inequality constrained least squares (ICLS) estimator is given. We provide two examples which illustrate the use of this closed form in the computation of estimates.Keywords
This publication has 10 references indexed in Scilit:
- Some results on the statistical properties of an inequality constrained least squares estimator in a linear model with two regressorsJournal of Econometrics, 1982
- Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression ParametersEconometrica, 1982
- Sampling properties of an inequality restricted estimatorEconomics Letters, 1981
- Methods of Estimation for Multi-Market Disequilibrium ModelsEconometrica, 1980
- A Branch-and-Bound Solution of a Restricted Least Squares ProblemTechnometrics, 1976
- Inequality Constrained Least-Squares EstimationJournal of the American Statistical Association, 1976
- A Restricted Least Squares ProblemTechnometrics, 1974
- Restricted Least Squares Regression and Convex Quadratic ProgrammingTechnometrics, 1969
- Inequality Restrictions in Regression AnalysisJournal of the American Statistical Association, 1966
- Nonlinear ProgrammingPublished by University of California Press ,1951