Some computational aspects of the generalized von Mises distribution |
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Authors: | Riccardo Gatto |
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Institution: | (1) Institute of Mathematical Statistics and Actuarial Science, University of Bern, Alpeneggstrasse 22, 3012 Bern, Switzerland |
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Abstract: | This article deals with some important computational aspects of the generalized von Mises distribution in relation with parameter
estimation, model selection and simulation. The generalized von Mises distribution provides a flexible model for circular
data allowing for symmetry, asymmetry, unimodality and bimodality. For this model, we show the equivalence between the trigonometric
method of moments and the maximum likelihood estimators, we give their asymptotic distribution, we provide bias-corrected
estimators of the entropy, the Akaike information criterion and the measured entropy for model selection, and we implement
the ratio-of-uniforms method of simulation. |
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Keywords: | Circular distribution Akaike information criterion Efficient score Entropy Fisher information Fourier series Kullback-Leibler information Maximum likelihood estimator Mixture distribution Ratio-of-uniforms method Trigonometric method of moments estimator |
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