Weighted Least Squares and Adaptive Least Squares: Further Empirical Evidence

dc.accessRightsAnonymous
dc.audienceScience
dc.contributor.authorSterchi, Martin
dc.contributor.authorWolf, Michael
dc.contributor.editorKreinovich, Vladik
dc.contributor.editorSriboonchitta, Songsak
dc.contributor.editorHuynh, Van-Nam
dc.date.accessioned2017-02-22T15:36:44Z
dc.date.available2017-04-19T13:18:18Z
dc.date.issued2017
dc.description.abstractThis paper compares ordinary least squares (OLS), weighted least squares (WLS), and adaptive least squares (ALS) by means of a Monte Carlo study and an application to two empirical data sets. Overall, ALS emerges as the winner: It achieves most or even all of the efficiency gains of WLS over OLS when WLS outperforms OLS, but it only has very limited downside risk compared to OLS when OLS outperforms WLS.
dc.description.urihttp://link.springer.com/chapter/10.1007/978-3-319-50742-2_9
dc.identifier.isbn978-3-319-50741-5
dc.identifier.urihttp://hdl.handle.net/11654/24445
dc.language.isoenen_US
dc.publisherSpringer
dc.relation.ispartofRobustness in Econometrics
dc.relation.ispartofseriesStudies in Computational Intelligence
dc.spatialHeidelberg
dc.titleWeighted Least Squares and Adaptive Least Squares: Further Empirical Evidence
dc.type04A - Beitrag Sammelband
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.IsStudentsWorkno
fhnw.PublishedSwitzerlandNo
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Wirtschaftde_CH
fhnw.affiliation.institutInstitute for Competitiveness and Communicationde_CH
fhnw.pagination135-167
fhnw.publicationStatePublished
fhnw.seriesNumber692
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