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Nonparametric multiple regression estimation for circular response

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URI: http://hdl.handle.net/2183/34329
DOI: 10.1007/s11749-020-00736-w

Publication date

2021

Authors

Crujeiras-Casais, Rosa M.
Panzera, Agnese

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Bibliographic citation

Meilán-Vila, A., Francisco-Fernández, M., Crujeiras, R.M. et al. Nonparametric multiple regression estimation for circular response. TEST 30, 650–672 (2021). https://doi.org/10.1007/s11749-020-00736-w

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Academic degree

Abstract

Nonparametric estimators of a regression function with circular response and -valued predictor are considered in this work. Local polynomial estimators are proposed and studied. Expressions for the asymptotic conditional bias and variance of these estimators are derived, and some guidelines to select asymptotically optimal local bandwidth matrices are also provided. The finite sample behavior of the proposed estimators is assessed through simulations, and their performance is also illustrated with a real data set.

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Versión final aceptada de: https://doi.org/10.1007/s11749-020-00736-w
This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect postacceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s11749-020-00736-w

Keywords

Linear–circular regression Multiple regression Local polynomial estimators

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https://link.springer.com/article/10.1007/s11749-020-00736-w

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