Computations for constrained linear models

Andrew Ronald Gallant, Thomas M. Gerig

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The article presents an algorithm for linear regression computations subject to linear parametric equality constraints, linear parametric inequality constraints, or a mixture of the two. No rank conditions are imposed on the regression specification or the constraint specification. The algorithm requires a full Moore-Penrose g-inverse which entails extra computational effort relative to other orthonormalization type algorithms. In exchange, auxiliary statistical information is generated: feasibility of a set of constraints may be checked, estimability of a linear parametric function may be checked, and bias and variance may be decomposed by source.

Original languageEnglish (US)
Pages (from-to)59-84
Number of pages26
JournalJournal of Econometrics
Volume12
Issue number1
DOIs
StatePublished - Jan 1 1980

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

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