Optimal testing for additivity in multiple nonparametric regression (Articolo in rivista)

Type
Label
  • Optimal testing for additivity in multiple nonparametric regression (Articolo in rivista) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/s10463-007-0164-y (literal)
Alternative label
  • Abramovich F.; De Feis I.; Sapatinas T. (2009)
    Optimal testing for additivity in multiple nonparametric regression
    in Annals of the Institute of Statistical Mathematics; Springer, Tokio (Giappone)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Abramovich F.; De Feis I.; Sapatinas T. (literal)
Pagina inizio
  • 691 (literal)
Pagina fine
  • 714 (literal)
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  • 61 (literal)
Rivista
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  • DOI 10.1007/s10463-007-0164-y (literal)
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  • 3 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
  • Google S (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Department of Statistics and Operations Research, Tel Aviv University, Israel. Istituto per le Applicazioni del Calcolo ``Mauro Picone\" Sede di Napoli, Consiglio Nazionale delle Ricerche, Italy. Department of Mathematics and Statistics, University of Cyprus, Nicosia, Cyprus. (literal)
Titolo
  • Optimal testing for additivity in multiple nonparametric regression (literal)
Abstract
  • We consider the problem of testing for additivity in the standard multiple nonparametric regression model. We derive optimal (in the minimax sense) non- adaptive and adaptive hypothesis testing procedures for additivity against the composite nonparametric alternative that the response function involves interactions of second or higher orders separated away from zero in L 2([0, 1] d )-norm and also possesses some smoothness properties. In order to shed some light on the theoretical results obtained, we carry out a wide simulation study to examine the finite sample performance of the proposed hypothesis testing procedures and compare them with a series of other tests for additivity available in the literature. (literal)
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