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  • 1
    Online Resource
    Online Resource
    Berlin : Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
    UID:
    edochu_18452_4262
    Format: 1 Online-Ressource (13 Seiten)
    ISSN: 1436-1086
    Series Statement: Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes 2003,2005,30
    Content: In some applications, the population characteristics of main interest can be found in the tails of the distribution function. The study of risk of extreme events will lead to the use of probability distributions and the scenarios that correspond to the tail of these distributions. Considering two approaches: parametric and nonparametric, the research emphasizes the assessment of distribution tails, assuming that underlying distributions are heavy tailed. Two heavy tailed distributions are considered: Generalized Pareto and Lognormal. The Maximum likelihood estimation method, using the complete sample, and using only the upper order statistics provide estimators of the parameters. Measures of Bias and Mean Squared Error of the estimators of the parameters, and the Conditional Mean Exceedence Functions of the distributions, are generated. The methodology for estimating population parameters, has potential applications in financial markets, quality control, assurance portfolios, monitoring of residual discharges, medical applications, design of environmental policies, or calibration and adjustment of processes and equipment. The main idea is to present, and analyze the methods used for the estimation, and some convergence problems when these two distribution functions are used in generating scenarios.
    Language: English
    URL: Volltext  (kostenfrei)
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