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On the Estimation of the Extreme-Value Index and Large Quantile Estimation
Open accessAbstract
This paper consists of two parts. An easy proof is given for the weak consistency of Pickands' estimate for the main parameter of an extreme-value distribution. Moreover, further natural conditions are given for strong consistency and for asymptotic normality of the estimate. Next a large quantile of a distribution is estimated by a combination of extreme or intermediate order statistics. This leads to an asymptotic confidence interval.
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Cites
Handbook of Mathematical Functions
McQuarrie, D. A. (1966) · American Journal of Physics · doi:10.1119/1.1972842 · Cited by 40,433
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Handbook of Quantile Regression
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Metadata
- Authors
- Dekkers, A. L. M., & Haan, L. D.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1989-12-01
- Volume
- 17
- Issue
- 4
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W2164931226
- Cited by
- 292
- References
- 1
- FWCI
- 5.51
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: On the Estimation of the Extreme-Value Index and Large Quantile Estimation. https://app.cochat.ai/papers/10.1214/aos/1176347396
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- Dekkers, A. L. M., & Haan, L. D. (1989). On the Estimation of the Extreme-Value Index and Large Quantile Estimation. The Annals of Statistics. https://doi.org/10.1214/aos/1176347396
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.