Kernel distribution estimation for grouped data
Tipus de documentArticle
Data publicació2019-12-17
EditorInstitut d'Estadística de Catalunya
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
Interval-grouped data appear when the observations are not obtained in continuous time, but monitored in periodical time instants. In this framework, a nonparametric kernel distribution estimator is proposed and studied. The asymptotic bias, variance and mean integrated squared error of the new approach are derived. From the asymptotic mean integrated squared error, a plug-in bandwidth is proposed. Additionally, a bootstrap selector to be used in this context is designed. Through a comprehensive simulation study, the behaviour of the estimator and the bandwidth selectors considering different scenarios of data grouping is shown. The performance of the different approaches is also illustrated with a real grouped emergence data set of Avena sterilis (wild oat).
CitacióReyes, M. [et al.]. Kernel distribution estimation for grouped data. "SORT", 17 Desembre 2019, vol. 43, núm. 2, p. 259-288.
ISSN1696-2281
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43.2.4.reyes-etal.zip | 313,1Kb | application/zip | Visualitza/Obre |