Calculation of confidence intervals for simulation output
Calculation of confidence intervals for simulation output
复制标题
计算模拟输出的置信区间
DOI：
10.1145/1029174.1029176
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
W. Holland
中科院分区：
文献类型：
--
作者：
R. Cheng;W. Holland
这篇文章关注的是计算仿真输出的置信区间，它依赖于两个可变性来源。一种称为<i>模拟变异性</i>，是由于在模拟本身中使用随机数引起的;另一种称为<i>参数变异性</i>，是由于输入参数未知，必须从观测数据中估计。三种方法来计算置信区间-传统的渐近正态性理论的方法，自助法和一种新的方法，它产生一个保守的近似的基础上进行两次模拟运行在精心选择的参数设置。它表明，传统的和引导方法提供类似程度的准确性，而新的方法有时可能是非常保守的，它可以计算在一小部分的计算时间的确切方法。
This article is concerned with the calculation of confidence intervals for simulation output that is dependent on two sources of variability. One, referred to as <i>simulation variability</i>, arises from the use of random numbers in the simulation itself; and the other, referred to as <i>parameter variability</i>, arises when the input parameters are unknown and have to be estimated from observed data. Three approaches to the calculation of confidence intervals are presented--the traditional asymptotic normality theory approach, a bootstrap approach and a new method which produces a conservative approximation based on performing just two simulation runs at carefully selected parameter settings. It is demonstrated that the traditional and bootstrap approaches provide similar degrees of accuracy and that whilst the new method may sometimes be very conservative, it can be calculated in a small fraction of the computational time of the exact methods.