Likelihood estimation of the extremal index
Likelihood estimation of the extremal index
复制标题
极值指数的似然估计
DOI：
10.1007/s10687-007-0034-2
复制
发表时间：
2007
期刊：
影响因子：
1.3
通讯作者：
M. Süveges
中科院分区：
文献类型：
--
作者：
M. Süveges
本文发展了Ferro和Segers（J.R. Stat.索科，Ser. B 65：545，2003）的极值指数的估计，并提出了一种新的变量的使用，减少基于点过程的特性的似然偏差。两个估计：最大似然估计和迭代最小二乘估计的基础上归一化的集群之间的差距进行了讨论。第一个提供了一个灵活的工具，用于平滑方法。给出了条件D^{（2）}（u_n）$的一个诊断，在此条件下极大似然是成立的.新的估计的性能进行了测试，通过广泛的模拟。英格兰中部温度序列的应用程序演示了使用最大似然估计与平滑方法。
The article develops the approach of Ferro and Segers (J.R. Stat. Soc., Ser. B 65:545, 2003) to the estimation of the extremal index, and proposes the use of a new variable decreasing the bias of the likelihood based on the point process character of the exceedances. Two estimators are discussed: a maximum likelihood estimator and an iterative least squares estimator based on the normalized gaps between clusters. The first provides a flexible tool for use with smoothing methods. A diagnostic is given for condition $D^{(2)}(u_n)$, under which maximum likelihood is valid. The performance of the new estimators were tested by extensive simulations. An application to the Central England temperature series demonstrates the use of the maximum likelihood estimator together with smoothing methods.