On the relationship between regression analysis and mathematical programming
type: Item
instance of: scholarly article
title: On the relationship between regression analysis and mathematical programming
zbMATH Open document ID: 1055.62082
DOI: 10.1155/S1173912604000082
author: D. Kharzeev
published in: Journal of Applied Mathematics and Decision Sciences
publication date: 2005-01-31T00:00:00Z
full work available at URL: https://eudml.org/doc/124200
review text: Summary: The interaction between linear and quadratic programming and regression analysis are explored by both statistical and operations research methods. Estimation and optimization problems are formulated in two different ways: on one hand linear and quadratic programming problems are formulated and solved by statistical methods, and on the other hand the solution of the linear regression model with constraints makes use of the simplex methods of linear or quadratic programming. Examples are given to illustrate the ideas.
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 90C90
Mathematics Subject Classification ID: 90C05
Mathematics Subject Classification ID: 90C20
zbMATH DE Number: 2131519
zbMATH Keywords: simplex method
zbMATH Keywords: two-phase methods
zbMATH Keywords: least squares method
zbMATH Keywords: quadratic programming
zbMATH Keywords: artificial variable
MaRDI profile type: Publication
OpenAlex ID: W2109088672
description: scientific article; zbMATH DE number 2131519