TY - JOUR
T1 - An algorithm for estimating the parameters in multiple linear regression model with linear constraints
AU - Wang, Hong
AU - Rhee, Wansoo T.
PY - 1995/1/1
Y1 - 1995/1/1
N2 - This paper develops an algorithm for estimating the parameters when the parameters are restricted by linear constraints in a general multiple regression model. The algorithm solves discrete approximation in the Φ error where Φ is a convex and symmetric function. These discrete approximations arise in fitting by polynomials, linear regression and goal programming. Discrete approximation problems in the L1 norm is a special case. The approaches to the solution of these approximation problems have a long history. The algorithm utilizes certain properties of the problem to significantly reduce the number of iterations to find the approximated solution. © 1995.
AB - This paper develops an algorithm for estimating the parameters when the parameters are restricted by linear constraints in a general multiple regression model. The algorithm solves discrete approximation in the Φ error where Φ is a convex and symmetric function. These discrete approximations arise in fitting by polynomials, linear regression and goal programming. Discrete approximation problems in the L1 norm is a special case. The approaches to the solution of these approximation problems have a long history. The algorithm utilizes certain properties of the problem to significantly reduce the number of iterations to find the approximated solution. © 1995.
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U2 - 10.1016/0360-8352(95)00011-O
DO - 10.1016/0360-8352(95)00011-O
M3 - Article
SN - 0360-8352
VL - 28
SP - 813
EP - 821
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
IS - 4
ER -