TECHNICAL PAPERS
Mar 1, 1992

Engineering Analysis of Extreme Value Data: Selection of Models

Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 118, Issue 2

Abstract

This paper discusses some of the existing statistical models for the analysis of extreme value data in the case of independence, pointing out their excellence and possible sources of error. Initially, the concept of order statistics is introduced, and the joint distribution of any set of order statistics is given. As simple examples, the distribution of the maximum, the minimum, any single order statistic, or any pair of order statistics are derived. Then, the problem of limit distribution is raised and carefully analyzed making a clear distinction between maxima and minima. It is shown that all models can be grouped in the Von Mises‐Jenkinson families, which include the three classical families. Several methods for selecting an adequate limit distribution based on data, including probability papers, least‐squares methods, and the curvature method are described. To clarify concepts, several illustrative examples of applications are included. Finally, a practical method for determining the limit distribution is described in detail.

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References

1.
Castillo, E. (1988). Extreme value theory in engineering. Academic Press, San Diego, Calif., 389.
2.
Castillo, E., and Galambos, J. (1986). Determining the domain of attraction of an extreme value distribution. Temple Univ., Philadelphia, Pa., 1–12.
3.
Castillo, E., Galambos, J., and Sarabia, J. M. (1989). “The selection of the domain of attraction of an extreme value distribution from a set of data.” Lecture Notes in Statistics, 51, 181–190.
4.
David, H. A. (1981). Order statistics. John Wiley and Sons, New York, N.Y.
5.
Fisher, R. A., and Tippett, L. H. C. (1928). “Limiting forms of the frequency distributions of the largest or smallest member of a sample.” Proc. Cambridge Philosophical Society, Cambridge, England, 24, 180–190.
6.
Galambos, J. (1987). The asymptotic theory of extreme order statistics. Robert Krieger Publishing Co., Malabar, Fla.
7.
Leadbetter, M. R., Lindgren, G., and Rootzén, H. (1983). Extremes and relate properties of random sequences and processes. Springer‐Verlag, New York, N.Y.
8.
Sarabia, J. M., and Castillo, E. (1989). “Una familia triparamétrica para aproximar distribuciones de extremos” (in Spanish). Proc. XIV Jornadas Hispano‐Lusas de Matemáticas, Tenerife, Spain, Vol. II, 1055–1059.

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Go to Journal of Waterway, Port, Coastal, and Ocean Engineering
Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 118Issue 2March 1992
Pages: 129 - 146

History

Published online: Mar 1, 1992
Published in print: Mar 1992

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Enrique Castillo
Prof., Escuela de Ingenieros de Caminos, Canales y Puertos, Universidad de Cantabria, Departamento de Matemática Aplicada y Ciencias de la Computatión, 39005 Santander, Spain
José María Sarabia
Prof., Facultad de Ciencias Económicas y Empresariales, Universidad de Cantabria, Departamento de Economía, 39005 Santander, Spain

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