Time-Varying Linear Regression Via Flexible Least Squares
This 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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|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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Web page: http://www.econ.iastate.edu
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