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The improved algorithms to estimate /spl alpha/ of alpha stable distribution based on empirical characteristic function

机译:基于经验特征函数的估计/ spl alpha / alpha稳定分布的改进算法

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The estimation of characteristic exponent /spl alpha/ is the most important step for the parameter estimation of symmetric /spl alpha/ stable distribution. For lack of closed form of probability density function (pdf), classical methods are no longer available. In this paper improved algorithms based on the empirical characteristic function are proposed to solve this problem under the conditions of short data samples. Simulations show that the proposed algorithms are robust and they are more efficient and applicable than the conventional ones.
机译:特征指数/ spl alpha /的估计是对称/ spl alpha /稳定分布的参数估计的最重要步骤。由于缺乏概率密度函数(pdf)的闭合形式,因此不再有经典方法。本文提出了一种基于经验特征函数的改进算法,以解决短数据样本条件下的问题。仿真表明,所提出的算法是鲁棒的,并且比常规算法更有效,更适用。

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