CircSiZer: an exploratory tool for circular data
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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.
KeywordsCircular data CircSiZer Nonparametric estimation Wind pattern
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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