TY - JOUR
T1 - Approximating Catastrophic Risk Through Statistics of Extremes
AU - MITSIOPOULOS, JAMES
AU - HAIMES, YACOV Y.
AU - LI, DUAN
PY - 1991/6
Y1 - 1991/6
N2 - This paper studies the approximation of the partitioned multiobjective risk method's (PMRM) extreme‐event risk function ƒ4. The analytic expression of the approximation for ƒ4 is derived through the use of the statistics of extremes for cases where the underlying distribution is of an extreme‐value type I, II, or III, and it thus provides an effective theoretical tool for understanding the behavior of conditional expected values for a large class of distribution functions used in science and engineering. The results are confirmed for example problems of normal, Gumbel, Weibull, Pareto, lognormal, and uniform distributions.
AB - This paper studies the approximation of the partitioned multiobjective risk method's (PMRM) extreme‐event risk function ƒ4. The analytic expression of the approximation for ƒ4 is derived through the use of the statistics of extremes for cases where the underlying distribution is of an extreme‐value type I, II, or III, and it thus provides an effective theoretical tool for understanding the behavior of conditional expected values for a large class of distribution functions used in science and engineering. The results are confirmed for example problems of normal, Gumbel, Weibull, Pareto, lognormal, and uniform distributions.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0026299137&origin=recordpage
U2 - 10.1029/91WR00333
DO - 10.1029/91WR00333
M3 - RGC 21 - Publication in refereed journal
SN - 0043-1397
VL - 27
SP - 1223
EP - 1230
JO - Water Resources Research
JF - Water Resources Research
IS - 6
ER -