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Non-parametric Regression for Circular Responses

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  • MARCO DI MARZIO
  • AGNESE PANZERA
  • CHARLES C. TAYLOR

Abstract

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  • Marco Di Marzio & Agnese Panzera & Charles C. Taylor, 2013. "Non-parametric Regression for Circular Responses," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(2), pages 238-255, June.
    • Handle: RePEc:bla:scjsta:v:40:y:2013:i:2:p:238-255
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    File URL: http://hdl.handle.net/10.1111/j.1467-9469.2012.00809.x
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    References listed on IDEAS

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    1. Marco Di Marzio & Charles Taylor, 2009. "Using small bias nonparametric density estimators for confidence interval estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(2), pages 229-240.
    2. Kato, Shogo & Jones, M. C., 2010. "A Family of Distributions on the Circle With Links to, and Applications Arising From, Möbius Transformation," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 249-262.
    3. Di Marzio, Marco & Panzera, Agnese & Taylor, Charles C., 2009. "Local polynomial regression for circular predictors," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 2066-2075, October.
    4. Macro Di Marzio & Agnese Panzera & Charles C. Taylor, 2012. "Non-parametric smoothing and prediction for nonlinear circular time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(4), pages 620-630, July.
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    Citations

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    Cited by:

    1. Andrea Meilán-Vila & Mario Francisco-Fernández & Rosa M. Crujeiras & Agnese Panzera, 2021. "Nonparametric multiple regression estimation for circular response," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 650-672, September.
    2. Andrade, Ana C.C. & Pereira, Gustavo H.A. & Artes, Rinaldo, 2023. "The circular quantile residual," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    3. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
    4. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    5. Cristina Rueda & Miguel A. Fernández & Sandra Barragán & Kanti V. Mardia & Shyamal D. Peddada, 2016. "Circular piecewise regression with applications to cell‐cycle data," Biometrics, The International Biometric Society, vol. 72(4), pages 1266-1274, December.
    6. Meisam Moghimbeygi & Mousa Golalizadeh, 2019. "A longitudinal model for shapes through triangulation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(1), pages 99-121, March.
    7. Marco Marzio & Stefania Fensore & Agnese Panzera & Charles C. Taylor, 2018. "Circular local likelihood," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(4), pages 921-945, December.
    8. Andrea Meilán-Vila & Rosa M. Crujeiras & Mario Francisco-Fernández, 2024. "Nonparametric estimation for a functional-circular regression model," Statistical Papers, Springer, vol. 65(2), pages 945-974, April.

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