Some computational aspects of the generalized von Mises distribution
Some computational aspects of the generalized von Mises distribution
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DOI：
10.1007/s11222-008-9060-4
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发表时间：
2008-09-01
影响因子：
2.2
通讯作者：
Gatto, Riccardo
中科院分区：
文献类型：
--
作者：
Gatto, Riccardo
本文讨论了与参数估计、模型选择和仿真相关的广义冯米塞斯分布的一些重要计算方面。广义冯米塞斯分布为循环数据提供了灵活的模型，允许对称、不对称、单峰和双峰。对于这个模型，我们展示了矩的三角方法和最大似然估计之间的等价性，我们给出了它们的渐近分布，我们提供了偏差校正的熵估计，Akaike信息准则和测量熵用于模型选择，并且我们实现了模拟的比值方法。
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.