基于平稳时间序列的随机测量程序

D. Monica
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引用次数: 1

摘要

随机测量程序已经在EQC上发表的几篇文章中提出和发展。与传统测量方法使用过时的误差传播公式来考虑测量不确定度不同,随机测量方法以自然合理的方式包含了测量过程的整个不确定度。本文将随机测量过程的概念推广到测量过程由随机过程或更准确地说由时间序列给出的情况。这种情况经常出现为经济现象。在本文中,只演示这种测量程序的可行性,因此考虑仅限于一些简单且相当不现实的例子。在实际情况下,必须根据随机建模的规则建立合适的随机模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic Measurement Procedures Based on Stationary Time Series
Stochastic measurement procedures have been proposed and developed in several articles published in EQC. In contrast to the traditional measurement procedures that use the obsolete error propagation formula for taking into account measurement uncertainty, stochastic measurement procedures include the entire uncertainty of the measurement process in a natural and rational way. In this paper the concept of stochastic measurement procedure is extended to the case that the measurement process is given by a stochastic process or more precisely said by a time series. This case appears often for economic phenomena. In this paper, only the feasibility of such measurement procedures shall be demonstrated and the considerations are therefore restricted to some simple and rather unrealistic examples. In a realistic case an appropriate stochastic model must be developed following the rules of stochastic modelling.
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