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October  2008, 4(4): 757-766. doi: 10.3934/jimo.2008.4.757

A selection problem for a constrained linear regression model

Shaoyong Lai 1, and  Qichang Xie 2,

1. 

College of Economic Mathematics, Southwestern University of Finance and Economics, Chengdu 610074, China
2. 

College of Economic Mathematics, Southwestern University of Finance and Economics, 610074, Chengdu, China

Received  February 2008 Revised  August 2008 Published  November 2008

Selecting a good estimate for a constricted linear regression model is investigated by using the generalized information criterion. Some asymptotic properties of the selection procedure with the model average technique are established. It is shown that the selection procedure is asymptotically efficient in the sense that a fitted estimate asymptotically obtains the minimum average squared error from a class of model average estimators.
Keywords: generalized information criterion, Model selection, optimality., constrained linear regression model.
Mathematics Subject Classification: Primary: 60G35; Secondary: 60J2.
Citation: Shaoyong Lai, Qichang Xie. A selection problem for a constrained linear regression model. Journal of Industrial & Management Optimization, 2008, 4 (4) : 757-766. doi: 10.3934/jimo.2008.4.757
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