The Annals of Applied Probability

Maxima of Poisson-like variables and related triangular arrays

Clive W. Anderson, Stuart G. Coles, and Jürg Hüsler

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Abstract

It is known that maxima of independent Poisson variables cannot be normalized to converge to a nondegenerate limit distribution. On the other hand, the Normal distribution approximates the Poisson distribution for large values of the Poisson mean, and maxima of random samples of Normal variables may be linearly scaled to converge to a classical extreme value distribution. We here explore the boundary between these two kinds of behavior. Motivation comes from the wish to construct models for the statistical analysis of extremes of background gamma radiation over the United Kingdom. The methods extend to row-wise maxima of certain triangular arrays, for which limiting distributions are also derived.

Article information

Source
Ann. Appl. Probab., Volume 7, Number 4 (1997), 953-971.

Dates
First available in Project Euclid: 29 January 2003

Permanent link to this document
https://projecteuclid.org/euclid.aoap/1043862420

Digital Object Identifier
doi:10.1214/aoap/1043862420

Mathematical Reviews number (MathSciNet)
MR1484793

Zentralblatt MATH identifier
0897.60052

Subjects
Primary: 60G70: Extreme value theory; extremal processes
Secondary: 60F10: Large deviations

Keywords
extreme values Poisson distribution large deviations triangular arrays regular variation subexponential distributions modelling of extremes radiation counts

Citation

Anderson, Clive W.; Coles, Stuart G.; Hüsler, Jürg. Maxima of Poisson-like variables and related triangular arrays. Ann. Appl. Probab. 7 (1997), no. 4, 953--971. doi:10.1214/aoap/1043862420. https://projecteuclid.org/euclid.aoap/1043862420


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