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Title: Circular data with error-in-variables Authors:  Marco Di Marzio - University of Chieti-Pescara (Italy) [presenting]
Stefania Fensore - University of Chieti-Pescara (Italy)
Agnese Panzera - University of Florence (Italy)
Charles C Taylor - University of Leeds (United Kingdom)
Abstract: Nonparametric methods are discussed for the case when data are observed with error and have a circular nature. Some classical approaches are explored, such as the deconvolution one, but also less popular ones, like bias reduction under the hypotesis of double asymptotics, and finally, some new resampling strategies. Proposals are justified by both asymptotic properties and simulative evidences.