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Statistical Estimation in Extreme Value Theory

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Part of the book series: NATO ASI Series ((ASIC,volume 131))

Abstract

If the maximum (or minimum) of a sample, properly standardized, has a nondegenerate limit distribution (as the sample size tends to ∞) then for every fixed k, the joint distribution of the k upper (lower) sample extremes converges to a nondegenerate limit. Based on this limiting distribution, if only sample extremes are available (e.g. in life testing situations) tail parameters can be consistently estimated.

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References

  • Boos, D.D., 1983, Using extreme value theory to estimate large percentiles, Technical report, Department of Statistics, North Carolina State University.

    Google Scholar 

  • Gumbel, E.J., 1958, Statistics of Extremes, Columbia University Press, New York.

    Google Scholar 

  • Hall, P., 1982, On estimating the endpoint of a distribution, Ann. of Statist. 10, pp. 556–568.

    Article  MATH  Google Scholar 

  • Hill, B.M., 1975, A simple general approach to inference about the tail of a distribution, Ann. of Statist. 3, pp. 1163–1174.

    Article  MATH  Google Scholar 

  • Pickands, J. III, 1975, Statistical inference using extreme Order Statistics, Ann. of Statist. 3, pp. 119–131.

    Article  MathSciNet  MATH  Google Scholar 

  • Smith, R.L. and Weissman, I., 1983, Maximum likelihood estimation of the lower tail of a probability distribution. (Unpublished).

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  • Weiss, L., 1971, Asymptotic inference about a density function at the end of its range, Nay. Res. Log. Quart. 18, pp. 111–114.

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  • Weissman, I., 1978, Estimation of parameters and large quantiles based on the k largest observations, JASA 73, pp. 812–815.

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  • Weissman, I., 1980, Estimation of tail parameters under type I censoring, Commun. Statist. A9 (11), pp. 1165–1175.

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  • Weissman, I., 1981, Confidence intervals for the threshold parameter, Commun. Statist. 10 (6), pp. 549–557.

    MathSciNet  Google Scholar 

  • Weissman, I., 1982, Confidence intervals for the threshold parameter II: Unknown shape parameter, Commun. Statist. All(21),pp. 2451–2474.

    Google Scholar 

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© 1984 Springer Science+Business Media Dordrecht

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Weissman, I. (1984). Statistical Estimation in Extreme Value Theory. In: de Oliveira, J.T. (eds) Statistical Extremes and Applications. NATO ASI Series, vol 131. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3069-3_8

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  • DOI: https://doi.org/10.1007/978-94-017-3069-3_8

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-8401-9

  • Online ISBN: 978-94-017-3069-3

  • eBook Packages: Springer Book Archive

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