Show simple item record

dc.contributor.authorRoca-Pardinas, J.
dc.contributor.authorRodríguez-Álvarez, M.X. 
dc.contributor.authorSperlich, S.
dc.date.accessioned2021-11-08T17:19:08Z
dc.date.available2021-11-08T17:19:08Z
dc.date.issued2021-01-01
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1378
dc.description.abstractA package is introduced that provides the weighted smooth backfitting estimator for a large family of popular semiparametric regression models. This family is known as generalized structured models, comprising, for example, generalized varying coefficient model, generalized additive models, mixtures, potentially including parametric parts. The kernel-based weighted smooth backfitting belongs to the statistically most efficient procedures for this model class. Its asymptotic properties are well-understood thanks to the large body of literature about this estimator. The introduced weights allow for the inclusion of sampling weights, trimming, and efficient estimation under heteroscedasticity. Further options facilitate easy handling of aggregated data, prediction, and the presentation of estimation results. Cross-validation methods are provided which can be used for model and bandwidth selection.1en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.titlePackage wsbackfit for Smooth Backfitting Estimation of Generalized Structured Modelsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doi10.32614/rj-2021-042en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/submittedVersionen_US
dc.journal.titleR Journalen_US
dc.volume.number13en_US
dc.issue.number1en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España