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Nonparametric estimation of a maximum of quantiles

: Enss, G.C.; Götz, B.; Kohler, M.; Krzyzak, A.; Platz, Roland


Electronic journal of statistics. Online journal 8 (2014), Nr.2, S.3176-3192
ISSN: 1935-7524
Deutsche Forschungsgemeinschaft DFG
SFB 805;
Fraunhofer LBF ()
nonparametric estimation

A simulation model of a complex system is considered which the outcome is described hy m(p, X), where p is a parameter of the system. X is a random input of the system and in is a real-valued function. The maximum (with respect to p) of the quantiles of m(p, X) is estimated. The quantiles of m(p, X) of a given level are estimated for various values of p from an order statistic of values m(p(i)., X-i) where X, X-1, X-2, ... are independent and identically distributed and where pi is close to p, and the maximal quantile is estimated by the maximum of these quantile estimates. Under assumptions on the smoothness of the function describing the dependency of the values of the quantiles on the parameter p the rate of convergence of this estimate is analyzed. The finite sample size behavior of the estimate is illustrated by simulated data and by applying it in a simulation model of a real mechanical system.