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Abstract

Chapter 1 is basic for the understanding of the main subjects treated in this book. It is assumed that the given data are generated according to a random mechanism that can be linked to some parametric statistical model.

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References

  1. Seal, H.L. (1969). Stochastic Theory of a Risk Business. Wiley, New York.

    MATH  Google Scholar 

  2. BĂĽuhlmann, H. (1970). Mathematical Methods in Risk Theory. Springer, Berlin.

    Google Scholar 

  3. Kolata, G. New views on life spans alter forecasts on elderly. The New York Times, Nov. 16. 1992.

    Google Scholar 

  4. We refer to Haight, F.A. (1967). Handbook of the Poisson Distribution. Wiley, New York; for a more recent monograph see Barbour, A.D., Holst, L. and Janson, S. (1992). Poisson Approximation. Oxford Studies in Probability. Oxford University Press.

    MATH  Google Scholar 

  5. Mises von, R. (1936). La distribution de la plus grande de n valeurs. Rev. Math. Union Interbalcanique 1, 141–160. Reproduced in Selected Papers of Richard von Mises, Amer. Math. Soc. 2 (1964), 271–294.

    Google Scholar 

  6. Jenkinson, A.F. (1955). The frequency distribution of annual maximum (or minimum) values of meteorological elements. Quart. J. Roy. Meteorol. Soc. 81, 158–171.

    Article  Google Scholar 

  7. Fisher, R.A. and Tippett, L.H.C. (1928). Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proc. Camb. Phil. Soc. 24, 180–190.

    Article  MATH  Google Scholar 

  8. Balkema, A.A. and de Haan, L. (1974). Residual life time at great age. Ann. Probab. 2, 792–804. Parallel work was done by J. Pickands (1975). Statistical inference using extreme value order statistics. Ann. Statist. 3, 119–131.

    MATH  Google Scholar 

  9. Drees, H. and Reiss, R.-D. (1992). Tail behavior in Wicksell’s corpuscle problem. In: Probability Theory and Applications, J. Galambos and I. Kátai (eds.), 205–220, Kluwer, Dortrecht.

    Google Scholar 

  10. Reiss, R.-D. (1989). Robust statistics: A converse view. 23rd Semester on Robustness and Nonparametric Statistics. Stefan Banach Center, Warsaw, Abstracts of Lectures, Part II, 183–184.

    Google Scholar 

  11. For details see, e.g., Devroye, L. (1986). Non-Uniform Random Variate Generation. Springer, New York.

    MATH  Google Scholar 

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© 2007 Birkhäuser Verlag AG

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(2007). Parametric Modeling. In: Statistical Analysis of Extreme Values. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-7399-3_1

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