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Technometrics Volume 21, 1979 - Issue 3
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Original Articles

Selection of Variables in Linear Regression Using the Minimum Sum of Weighted Absolute Errors Criterion

Subhash C. Narula School of Management Rensselaer Polytechnic Institute, Troy, NY, 12181
&
John F. Wellington Department of Business Administration, The Behrend College Pennsylvania State University, Erie, PA, 16563
Pages 299-306 | Published online: 09 Apr 2012

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Erich A. Joachimsthaler & Antonie Stam. (1990) Mathematical Programming Approaches for the Classification Problem in Two-Group Discriminant Analysis. Multivariate Behavioral Research 25:4, pages 427-454.
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Subhash C. Narula. (1987) The Minimum Sum of Absolute Errors Regression. Journal of Quality Technology 19:1, pages 37-45.
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Ronald D. Armstrong & Philip 0. Beck. (1986) The best subset of parameters in min-max linear regression. Communications in Statistics - Simulation and Computation 15:1, pages 263-270.
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Terry E. Dielman & Roger C. Pfaffenberger. (1984) Computational Algorithms for Calculating Least Absolute Value and Chebyshev Estimates for Multiple Regression. American Journal of Mathematical and Management Sciences 4:1-2, pages 169-197.
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R.R. Hocking. (1983) Developments in Linear Regression Methodology: 1959–l982. Technometrics 25:3, pages 219-230.
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Subhash C. Narula & John F. Wellington. (1983) Selection of variables in linear regression: a pragmatic approach. Journal of Statistical Computation and Simulation 17:3, pages 159-172.
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Articles from other publishers (18)

Fusheng Xiong, Michael Kuby & Wayne D. Frasch. 2020. Novel Trends in the Traveling Salesman Problem. Novel Trends in the Traveling Salesman Problem.
Kenneth J. Berry, Janis E. Johnston & Paul W. MielkeKenneth J. Berry, Janis E. Johnston & Paul W. MielkeJr.Jr.. 2014. A Chronicle of Permutation Statistical Methods. A Chronicle of Permutation Statistical Methods 199 274 .
Dimitris Bertsimas & Romy Shioda. (2007) Algorithm for cardinality-constrained quadratic optimization. Computational Optimization and Applications 43:1, pages 1-22.
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D. M. Hawkins. 2004. Encyclopedia of Statistical Sciences. Encyclopedia of Statistical Sciences.
D. M. Hawkins. 2004. Encyclopedia of Statistical Sciences. Encyclopedia of Statistical Sciences.
Carmen D. S. André, Subhash C. Narula, Silvia N. Elian & Rodrigo A. Tavares. (2003) An overview of the variables selection methods for the minimum sum of absolute errors regression. Statistics in Medicine 22:13, pages 2101-2111.
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E.M.A.M. Mendez & S.A. Billings. (2001) An alternative solution to the model structure selection problem. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 31:6, pages 597-608.
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Subhash C. Narula, Paulo H. N. Saldiva, Carmen D. S. Andre, Silvia N. Elian, Aurea Favero Ferreira & Vera Capelozzi. (1999) The minimum sum of absolute errors regression: a robust alternative to the least squares regression. Statistics in Medicine 18:11, pages 1401-1417.
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M.J. Kuby, R.S. Cerveny & R.I. Dorn. (1997) A new approach to paleoclimatic research using linear programming. Palaeogeography, Palaeoclimatology, Palaeoecology 129:3-4, pages 251-267.
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T.K. Gustafsson & P.M. Mäkilä. (1996) Modelling of uncertain systems via linear programming. Automatica 32:3, pages 319-335.
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T.K. Gustafsson & P.M. Mäkilä. (1993) Modelling of Uncertain Systems via Linear Programming. IFAC Proceedings Volumes 26:2, pages 29-34.
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T.K. Gustafsson & P.M. Makila. (1993) On system identification and model validation via linear programming. On system identification and model validation via linear programming.
Helmuth Späth. 1992. Mathematical Algorithms for Linear Regression. Mathematical Algorithms for Linear Regression 17 192 .
Ronald D. Armstrong & P. O. Beck. (2006) Penalty calculations and branching rules in a LAV best subset procedure. Naval Research Logistics Quarterly 32:3, pages 407-415.
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Subhash C. Narula & John F. Wellington. (1985) A Branch and Bound Procedure for Selection of Variables in Minimax Regression. SIAM Journal on Scientific and Statistical Computing 6:3, pages 573-581.
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R. D. Armstrong, P. O. Beck & M. T. Kung. (1984) Algorithm 615: the best subset of parameters in leasst absolute value regression. ACM Transactions on Mathematical Software 10:2, pages 202-206.
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U. Peters & C. Willms. (1983) Up- and down-dating procedures for linearL 1 regression. Operations-Research-Spektrum 5:4, pages 229-239.
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Ronald D. Armstrong & Philip O. Beck. (1983) The best parameter subset using the Chebychev curve fitting criterion. Mathematical Programming 27:1, pages 64-74.
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