Voit E O, Schwacke L H
Department of Biometry and Epidemiology, Medical University of South Carolina, Charleston 29425, USA.
Risk Anal. 2000 Feb;20(1):59-71. doi: 10.1111/0272-4332.00006.
Monte Carlo simulations have become a mainstream technique for environmental and technical risk assessments. Because their results are dependent on the quality of the involved input distributions, it is important to identify distributions that are flexible enough to model all relevant data yet efficient enough to allow thousands of evaluations necessary in a typical simulation analysis. It has been shown in recent years that the S-distribution provides accurate representations for frequency data that are symmetric or skewed to either side. This flexibility makes the S-distribution an ideal candidate for Monte Carlo analyses. To use the distribution effectively, methods must be available for drawing S-distributed random numbers. Such a method is proposed here. It is shown that S-distributed random numbers can be efficiently generated from a simple algebraic formula whose coefficients are tabulated. The method is shown step by step and illustrated with a detailed example. (The tables are accessible in electronic form in the FTP parent directory at http:@www.musc.edu/voiteo/ftp/.)
蒙特卡罗模拟已成为环境和技术风险评估的主流技术。由于其结果取决于所涉及输入分布的质量,因此识别出足够灵活以对所有相关数据进行建模但又足够高效以允许在典型模拟分析中进行数千次评估的分布非常重要。近年来已表明,S分布能为对称或向两侧偏斜的频率数据提供准确表示。这种灵活性使S分布成为蒙特卡罗分析的理想候选者。为了有效使用该分布,必须有生成S分布随机数的方法。本文提出了这样一种方法。结果表明,可以从一个系数已制成表格的简单代数公式高效生成S分布随机数。该方法将逐步展示并通过一个详细示例进行说明。(这些表格可通过电子形式在http:@www.musc.edu/voiteo/ftp/的FTP父目录中获取。)