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The Riesz probability distribution: Generation and EM algorithm

机译:RIESZ概率分布:生成和EM算法

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The Riesz probability distribution was introduced in 2001 as an extension of the Wishart one. Although the Wishart distribution was investigated in many engineering applications, the Riesz applicability seems to be forsaken. This can be explained by the lack of studies offering statistical models and algorithms dealing with this distribution. Within this framework, we extend the Bartlett decomposition to the Riesz and inverse Riesz probability distributions. We prove that they can be generated easily using gamma and Gaussian independent variates adequately parameterized. Then we develop an Expectation-Maximization algorithm to estimate the parameters of the Riesz mixture model, along with the inverse Riesz mixture. Finally, some simulations are conducted and show a good estimation of the mixture parameters and clusters number.
机译:RIESZ概率分布于2001年推出,作为Wishart一个的延伸。虽然在许多工程应用中调查了Wishart分配,但riesz适用性似乎是令人讨厌的。这可以通过缺乏提供统计模型和处理此分布的算法的研究来解释。在此框架内,我们将Bartlett分解扩展到RIESZ和逆RIESZ概率分布。我们证明他们可以使用伽马和高斯独立变体进行充分参数化轻松生成。然后我们开发期望最大化算法来估计Riesz混合模型的参数,以及逆Riesz混合物。最后,进行了一些模拟,并显示出对混合参数和簇数的良好估计。

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