Wavelet density estimation for weighted data (Articolo in rivista)

Type
Label
  • Wavelet density estimation for weighted data (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.jspi.2013.09.015 (literal)
Alternative label
  • Cutillo, L.a and De Feis, I.b and Nikolaidou, C.c and Sapatinas, T.c (2014)
    Wavelet density estimation for weighted data
    in Journal of statistical planning and inference (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Cutillo, L.a and De Feis, I.b and Nikolaidou, C.c and Sapatinas, T.c (literal)
Pagina inizio
  • 1 (literal)
Pagina fine
  • 19 (literal)
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  • cited By (since 1996)0; Article in Press (literal)
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  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84885794891&partnerID=40&md5=cf1b0a1ec6a9290a1610b87da3542fda (literal)
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  • 146 (literal)
Rivista
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  • 19 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
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  • Dipartimento di Statistica e Matematica per la Ricerca Economica, Università degli studi di Napoli 'Parthenope, Via Generale Parisi n. 13, Naples, Italy; Istituto per le Applicazioni del Calcolo M. Picone (CNR), Naples, Italy; Department of Mathematics and Statistics, University of Cyprus, Cyprus (literal)
Titolo
  • Wavelet density estimation for weighted data (literal)
Abstract
  • We consider the estimation of a density function on the basis of a random sample from a weighted distribution. We propose linear and nonlinear wavelet density estimators, and provide their asymptotic formulae for mean integrated squared error. In particular, we derive an analogue of the asymptotic formula of the mean integrated square error in the context of kernel density estimators for weighted data, admitting an expansion with distinct squared bias and variance components. For nonlinear wavelet density estimators, unlike the analogous situation for kernel or linear wavelet density estimators, this asymptotic formula of the mean integrated square error is relatively unaffected by assumptions of continuity, and it is available for densities which are smooth only in a piecewise sense. We illustrate the behavior of the proposed linear and nonlinear wavelet density estimators in finite sample situations both in simulations and on a real-life dataset. Comparisons with a kernel density estimator are also given. © 2013 Elsevier B.V. All rights reserved. (literal)
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