Kernel smoothing density estimate for circular data
Updated 19 Nov 2014
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.
Vlad Atanasiu (2023). Kernel smoothing density estimate for circular data (https://www.mathworks.com/matlabcentral/fileexchange/32614-kernel-smoothing-density-estimate-for-circular-data), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Descriptive Statistics and Visualization >
Inspired by: Circular Statistics Toolbox (Directional Statistics)
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