Advances in Decision Sciences
Volume 8 (2004), Issue 2, Pages 131-140
doi:10.1155/S1173912604000082
On the relationship between regression analysis and mathematical programming
Dong Qian Wang1
, Stefanka Chukova1
and C.D. Lai3
1School of Mathematical and Computing Sciences, Victoria University of Wellington, New Zealand
3Institute of Information Sciences and Technology, Massey University, Palmerston North, New Zealand
Abstract
The interaction between linear, 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.