Di Marzio, M, Fensore, S, Panzera, A et al. (1 more author) (2020) Kernel Circular Deconvolution Density Estimation. In: ISNPS 2018. 4th ISNPS: Conference of the International Society for Non-Parametric Statistics, 11-15 Jun 2018, Salerno, Italy. Springer International Publishing , pp. 183-191. ISBN 9783030573058
Abstract
We consider the problem of nonparametrically estimating a circular density from data contaminated by angular measurement errors. Specifically, we obtain a kernel-type estimator with weight functions that are reminiscent of deconvolution kernels. Here, differently from the Euclidean setting, discrete Fourier coefficients are involved rather than characteristic functions. We provide some simulation results along with a real data application.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2020. This is an author produced version of a conference paper published in ISNPS 2018. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Circular kernels; Deconvolution; Fourier coeffcients; Measurement errors; Movements of ants |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Jan 2021 16:07 |
Last Modified: | 12 Nov 2021 01:38 |
Status: | Published |
Publisher: | Springer International Publishing |
Identification Number: | 10.1007/978-3-030-57306-5_17 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169475 |