数字仿真中初始化偏差消除方法综述

Annual Simulation Symposium Pub Date : 1987-06-01 DOI:10.1145/41824.41834

D. Kimbler, Barry D. Knight

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引用次数: 10

摘要

数字仿真中的初始化偏差通常出现在从复制数据估计稳态统计量时。虽然已经开发了一些方法来避免这种偏差，例如批处理方法，但在某些模拟环境中问题仍然存在。本报告调查了目前处理这种偏见的方法，并评估了它们的有效性和有用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A survey of current methods for the elimination of initialization bias in digital simulation

Initialization bias in digital simulation typically arises in estimating a steady-state statistic from replicated data. While methods have been developed to avoid this bias, such as batch means, the problem remains in some simulation contexts. This report surveys current methods for dealing with this bias and assesses their effectiveness and usefulness.

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Annual Simulation Symposium

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