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CircSiZer: an exploratory tool for circular data

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Abstract

Smoothing methods and SiZer (SIgnificant ZERo crossing of the derivatives) are useful tools for exploring significant underlying structures in data samples. An extension of SiZer to circular data, namely CircSiZer, is introduced. Based on scale-space ideas, CircSiZer presents a graphical device to assess which observed features are statistically significant, both for density and regression analysis with circular data. The method is intended for analyzing the behavior of wind direction in the atlantic coast of Galicia (NW Spain) and how it has an influence over wind speed. The performance of CircSiZer is also checked with some simulated examples.

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Acknowledgments

This work has been supported by Project MTM2008-03010 from the Spanish Ministry of Science and Innovation, and by the IAP network StUDyS (Developing crucial Statistical methods for Understanding major complex Dynamic Systems in natural, biomedical and social sciences), from Belgian Science Policy. We also acknowledge the advice of José A. Crujeiras, an experienced skipper working in the Galician coast.

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Authors and Affiliations

  1. Department of Statistics and Operations Research, University of Santiago de Compostela, Galicia, Spain

    María Oliveira, Rosa M. Crujeiras & Alberto Rodríguez-Casal

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  1. María Oliveira
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  2. Rosa M. Crujeiras
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  3. Alberto Rodríguez-Casal
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Correspondence to María Oliveira.

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Handling Editor: Ashis SenGupta.

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Oliveira, M., Crujeiras, R.M. & Rodríguez-Casal, A. CircSiZer: an exploratory tool for circular data. Environ Ecol Stat 21, 143–159 (2014). https://doi.org/10.1007/s10651-013-0249-0

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  • DOI: https://doi.org/10.1007/s10651-013-0249-0

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