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Semiparametric topographical mixture models with symmetric errors

  • Université Gustave Eiffel
  • IBM Watson Research Center
  • College of Computing

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

Motivated by the analysis of a Positron Emission Tomography (PET) imaging data considered in Bowen et al. [Radiother. Oncol. 105 (2012) 41-48], we introduce a semiparametric topographical mixture model able to capture the characteristics of dichotomous shifted response-type experiments. We propose a pointwise estimation procedure of the proportion and location functions involved in our model. Our estimation procedure is only based on the symmetry of the local noise and does not require any finite moments on the errors (e.g., Cauchy-type errors). We establish under mild conditions minimax properties and asymptotic normality of our estimators. Moreover, Monte Carlo simulations are conducted to examine their finite sample performance. Finally, a statistical analysis of the PET imaging data in Bowen et al. is illustrated for the proposed method.

langue originaleAnglais
Pages (de - à)825-862
Nombre de pages38
journalBernoulli
Volume23
Numéro de publication2
Les DOIs
étatPublié - 1 mai 2017
Modification externeOui

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