Time-Varying Linear Regression Via Flexible Least Squares
AbstractThis article develops a multicriteria "flexible least squares (FLS)" method for time-varying linear regression. The basic FLS objective is to determine the "residual efficiency frontier," that is, the set of all coefficient trajectory estimates that yield vector-minimal sums of squared residual measurement and dynamic errors conditional on a given set of observations. The FLS algorithm was incorporated into the statistical packages GAUSS/TSM and SHAZAM in 1997. Annotated pointers to related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/flshome.htm
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 11196.
Date of creation: 01 Jan 1989
Date of revision:
Publication status: Published in Computers and Mathematics With Applications 1989, vol. 17 no. 08/09/09, pp. 1215-1245
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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
Phone: +1 515.294.6741
Fax: +1 515.294.0221
Web page: http://www.econ.iastate.edu
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- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
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