Identification of individual aberrations in least squares regression
Citation:
R.C. Geary, 'Identification of individual aberrations in least squares regression', Economic and Social Research Institute, Economic and Social Review, Vol.2 (Issue 4), 1971, 1971, pp429-438Download Item:
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Abstract:
In single equation LS regression the common practice is. to test goodness-of- fit by the standard error o f estimate s and probable absence, of residual autoregression by the Durbin-Watson d, or the more recent count Of sign changes r. With a wide choice of causative (or independent) variables (indvars) and With access to a computer, a multitude of regressions can be produced, one for each set o f indvars selected. We usually pick the regression with the lowest s and a satisfactory d or r as the 'best', unless there are very compelling a priori reasons for picking some other set. Truth to say, there is still much empiricism in regression practice; in it art has a place as well as science.
Author: Geary, R.C.
Publisher:
Economic & Social StudiesType of material:
Journal ArticleCollections:
Series/Report no:
Economic and Social ReviewVol.2 (Issue 4), 1971
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MathematicsISSN:
0012-9984Licences: