Estimating the concentration parameter of a von Mises distribution: a systematic simulation benchmark
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In directional statistics, the von Mises distribution is a key element in the analysis of circular data. While there is a general agreement regarding the estimation of its location parameter μ, several methods have been proposed to estimate the concentration parameter κ. We here provide a thorough evaluation of the behavior of 12 such estimators for datasets of size N ranging from 2 to 8 192 generated with a κ ranging from 0 to 100. We provide detailed results as well as a global analysis of the results, showing that (1) for a given κ, most estimators have behaviors that are very similar for large datasets (N ≥ 16) and more variable for small datasets, and (2) for a given estimator, results are very similar if we consider the mean absolute error for κ≤ 1 and the mean relative absolute error for κ≥ 1.
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