59236

Автор(ов): 

1

Параметры публикации
Тип публикации: 
Глава в книге
Название: 
The Discrepancy Method for Extremal Index Estimation
ISBN/ISSN: 
978-3-030-57305-8
DOI: 
10.1007/978-3-030-57306-5_31
Наименование источника: 
Nonparametric Statistics
Город: 
Cham
Издательство: 
Springer
Год издания: 
2020
Страницы: 
341-355
Аннотация
We consider the nonparametric estimation of the extremal index of stochastic processes. The discrepancy method that was proposed by the author as a data-driven smoothing tool for probability density function estimation is extended to find a threshold parameter u for an extremal index estimator in case of heavy-tailed distributions. To this end, the discrepancy statistics are based on the von Mises–Smirnov statistic and the k largest order statistics instead of an entire sample. The asymptotic chi-squared distribution of the discrepancy measure is derived. Its quantiles may be used as discrepancy values. An algorithm to select u for an estimator of the extremal index is proposed. The accuracy of the discrepancy method is checked by a simulation study.
Библиографическая ссылка: 
Маркович Н.М. The Discrepancy Method for Extremal Index Estimation / Nonparametric Statistics. Cham: Springer, 2020. С. 341-355.