Nonparametric multiple regression estimation for circular response

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Nonparametric multiple regression estimation for circular responseFecha
2021Cita bibliográfica
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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https://doi.org/10.1007/s11749-020-00736-w
Resumen
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.
Palabras clave
Linear–circular regression
Multiple regression
Local polynomial estimators
Multiple regression
Local polynomial estimators
Descripción
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
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