التفاصيل البيبلوغرافية
| العنوان: |
Nonparametric estimator of the tail dependence coefficient: balancing bias and variance. |
| المؤلفون: |
Garcin, Matthieu1 (AUTHOR) matthieu.garcin@m4x.org, Nicolas, Maxime L. D.2 (AUTHOR) |
| المصدر: |
Statistical Papers. Oct2024, Vol. 65 Issue 8, p4875-4913. 39p. |
| مصطلحات موضوعية: |
*ALGORITHMS, NONPARAMETRIC estimation, CENSORSHIP |
| مستخلص: |
A theoretical expression is derived for the mean squared error of a nonparametric estimator of the tail dependence coefficient, depending on a threshold that defines which rank delimits the tails of a distribution. We propose a new method to optimally select this threshold. It combines the theoretical mean squared error of the estimator with a parametric estimation of the copula linking observations in the tails. Using simulations, we compare this semiparametric method with other approaches proposed in the literature, including the plateau-finding algorithm. [ABSTRACT FROM AUTHOR] |
|
Copyright of Statistical Papers is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Business Source Index |