广义稳定过程的统计推断

The Statistical Inference for Generalized Stable Processes

  • 摘要: 本文应用Itô随机分析的方法证明了广义稳定过程依赖于0,t时间内跳量绝对值不小于ε(ε>0)的样本信息作出的参数的最大似然估计,当ε固定,t→∞,及当t固定,ε→0时都是强相合的,并证明了所有强相合估计的a.s.收敛速度符合重对数律。

     

    Abstract: By using the Itô calculus, the maximum likelihood estimators of the paramaters of generalized stable processes based on the information, on a given time interval 0, t, of the jumps of size greater than or equal to ε are proved to be strongly consistent not only as t tends to infinity, while ε is fixed, but also as ε tends to 0 and t is fixed. Moreover, we also prove that the convergent rates fit the law of the iterated logarithm for the strongly consistent estimators.

     

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