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中文摘要：
为了高效估计出K分布的参数,提出了对数累积量参数估计方法。基于第二类统计量,先对K分布的概率密度函数进行Mellin变换,从而获得K分布的第二类第一特征函数;然后对第二类第一特征函数进行对数变换,由此获得K分布的第二类第二特征函数;最后对第二类第二特征函数求导数,进而获得K分布的前两阶对数累积量,由此可以估计K分布的参数。与传统的最大似然估计方法相比,K分布的对数累积量估计具有解析的表达式,易于计算。Monte Carlo仿真表明,基于第二类统计量的K分布对数累积量估计可获得较高的估计精度。
英文摘要：
In order to efficiently estimate the parameters of K distribution,this paper proposed the log-cumulant estimator.Based on second-kind statistics,first it derived the second-kind first characteristic function of K distribution by taking the Mellin transformation to the probability density function of K distribution,second obtained the second-kind second cha-racteristic function of K distribution from the logarithmic transformation of the second-kind first characteristic function,and last deduced the first two log-cumulants to estimate the parameters of K distribution by taking the derivative of the second-kind second characteristic function.Compared to the traditional maximum likelihood estimator,the log-cumulant estimator of K distribution with analytical expressions was easy to compute.Monte Carlo simulations demonstrate that the log-cumulant estimator of K distribution based on second-kind statistics achieves high estimation accuracy.
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