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Goodness-of-fit tests for multiple regression with circular response

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http://hdl.handle.net/2183/34361
Atribución-NoComercial-SinDerivadas 3.0 España
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Title
Goodness-of-fit tests for multiple regression with circular response
Author(s)
Meilán-Vila, Andrea
Francisco-Fernández, Mario
Crujeiras-Casais, Rosa M.
Date
2022
Citation
A. Meilán-Vila, M. Francisco-Fernández & R.M. Crujeiras (2022) Goodness-of-fit tests for multiple regression with circular response, Journal of Statistical Computation and Simulation, 92:9, 1941-1963, DOI: 10.1080/00949655.2021.2015597
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10.1080/00949655.2021.2015597
Abstract
[Abstract]: Testing procedures for assessing a parametric regression model with a circular response and an Rd-valued covariate are proposed and analysed in this work. The test statistics are based on a circular distance comparing a (non-smoothed or smoothed) parametric circular regression estimator and a nonparametric one. Two bootstrap procedures for calibrating the tests in practice are also presented. Finite sample performance of the tests in different scenarios is analysed by simulations and illustrated with real data examples.
Keywords
Model checking
Circular data
Local linear regression
Bootstrap
 
Description
Versión final aceptada de: https://doi.org/10.1080/00949655.2021.2015597
 
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Statistical Computation and Simulation on 2022, available at: https://doi.org/10.1080/00949655.2021.2015597
 
Editor version
https://doi.org/10.1080/00949655.2021.2015597
Rights
Atribución-NoComercial-SinDerivadas 3.0 España

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