Transport investment decisions with Bayesian statistical decision theory

Daniel Shefer
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引用次数: 1

Abstract

This paper presents an optimal decision making process under uncertainty. The basic elements of the Bayesian Statistical Decision Theory which provides the basic framework of the analysis is being presented along with the elements of the traditional statistical decision theory. Subsequently, a simplified example of transport investment decisions is presented where Bayesian Statistics provides the basic elements of future uncertainty. Finally, the example presented is transformed into a computerized program amenable to rapid examination of multiple future events.

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基于贝叶斯统计决策理论的交通投资决策
提出了不确定条件下的最优决策过程。提供分析基本框架的贝叶斯统计决策理论的基本要素与传统统计决策理论的要素一起被提出。随后,提出了一个交通投资决策的简化示例,其中贝叶斯统计提供了未来不确定性的基本要素。最后,给出的例子被转换成一个计算机程序,以适应对多个未来事件的快速检查。
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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