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dc.contributor.authorGeary, R.C.
dc.date.accessioned2014-04-24T14:42:10Z
dc.date.available2014-04-24T14:42:10Z
dc.date.issued1971
dc.identifier.citationR.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, pp429-438
dc.identifier.issn0012-9984
dc.identifier.urihttp://hdl.handle.net/2262/68862
dc.description.abstractIn 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.
dc.language.isoen
dc.publisherEconomic & Social Studies
dc.relation.ispartofseriesEconomic and Social Review
dc.relation.ispartofseriesVol.2 (Issue 4), 1971
dc.subjectMathematics
dc.titleIdentification of individual aberrations in least squares regression
dc.typeJournal Article
dc.status.refereedYes
dc.publisher.placeDUBLIN
dc.rights.ecaccessrightsOpenAccess
dc.format.extentpaginationpp429-438


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