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利用经验特征函数估计柯西分布的位置与尺度AI 解读

The iterative method for the parameter estimation of stable laws proposed by Koutrouvelis (1981) is modified to handle the case where the distribution is assumed to belong to a Cauchy family with location and/or scale parameter unknown. It is shown that the determination of optimum values at which the empirical characteristic function needs to be evaluated reduces in this case to the determination of the asymptotically optimum quantiles for the parameter estimation of an…

利用经验特征函数估计柯西分布的位置与尺度AI 解读

SUMMARY The iterative method for the parameter estimation of stable laws proposed by Koutrouvelis (1981) is modified to handle the case where the distribution is assumed to belong to a Cauchy family with location and/or scale parameter unknown. It is shown that the determination of optimum values at which the empirical characteristic function needs to be evaluated reduces in this case to the determination of the asymptotically optimum quantiles for the parameter estimation…

稳定分布参数的回归型估计AI 解读

A regression-type method of estimating the four parameters of a stable distribution is presented. The estimators found are consistent and approximately unbiased for moderately large sample sizes. Their efficiencies, found through a simulation study, are greater than those of most other estimators for large portions of the parameter space. Moreover, the amount of computation involved is minimal and apparently less than that needed by the methods of Paulson, Holcomb, and…