Kernel smoothing density estimate for circular data
Provides various methods to smooth circular data.
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This is a companion to Matlab's Statistics toolbox ksdensity function and Philipp Berens' CircStat toolbox.
The difference with Matlab's ksdensity function is that this function is adaped to circular data, such as wind orientation. Using Matlab's function will give biased values at the extremities of the pdf for circular data.
The kernel used in this function is a normal distribution with an automatically computed optimal standard deviation as presented in:
- Silverman B. W. (1998), Density Estimation for Statistics and Data Analysis, Chapman & Hall / CRC, Boca Raton (FL), 47-8.
- Bowman Adrian W. & Adelchi Azzalini (1997) - Applied Smoothing Techniques for Data Analysis, Oxford University Press, 31.
- Wand M. P. & M. C. Jones (1995) - Kernel Smoothing, Chapman & Hall, London, 60-3.
Cite As
Vlad Atanasiu (2026). Kernel smoothing density estimate for circular data (https://uk.mathworks.com/matlabcentral/fileexchange/32614-kernel-smoothing-density-estimate-for-circular-data), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: Circular Statistics Toolbox (Directional Statistics)
General Information
- Version 1.4 (29.2 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
