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Statistical Inference Using Extreme Order Statistics
Open accessAbstract
A method is presented for making statistical inferences about the upper tail of a distribution function. It is useful for estimating the probabilities of future extremely large observations. The method is applicable if the underlying distribution function satisfies a condition which holds for all common continuous distribution functions.
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Citations
Cited by
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
Pimentel, M. A. F., Clifton, D. A., Clifton, L., & Tarassenko, L. (2014) · Signal Processing · doi:10.1016/j.sigpro.2013.12.026 · Cited by 1,649
Value-at-Risk Prediction: A Comparison of Alternative Strategies
Kuester, K. (2005) · Journal of Financial Econometrics · doi:10.1093/jjfinec/nbj002 · Cited by 632
Estimation of Parameters and Large Quantiles Based on the k Largest Observations
Weissman, I. (1978) · Journal of the American Statistical Association · doi:10.1080/01621459.1978.10480104 · Cited by 462
Handbook of Quantile Regression
(2017) · doi:10.1201/9781315120256 · Cited by 392
Metadata
- Authors
- III, J. P.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1975-01-01
- Volume
- 3
- Issue
- 1
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W2036983007
- Cited by
- 3,567
- References
- 0
- FWCI
- 1.18
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Statistical Inference Using Extreme Order Statistics. https://app.cochat.ai/papers/10.1214/aos/1176343003
- The paper
- III, J. P. (1975). Statistical Inference Using Extreme Order Statistics. The Annals of Statistics. https://doi.org/10.1214/aos/1176343003
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
