Moments and maximum entropy method for expanded uncertainty estimation in measurements

Arvind Rajan, Ye Chow Kuang, Melanie Po Leen Ooi, Serge N. Demidenko

    Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

    8 Citations (Scopus)


    The normal approximation and Monte Carlo simulation methods are widely used in the metrology to evaluate the expanded uncertainty, whereby the latter method is known to be the most robust and reliable. In some cases, however, (e.g., when the probability distribution is not known a priori) different frameworks may be desired as an alternative to the aforementioned techniques. One of them is commonly used in metrology-it is the moment (or cumulant)-based method. In view of that, and specifically for the scope of the expanded uncertainty estimation, this paper studies the theoretical viability of using high-order moments. It also analyzes the performance of a relatively new parametric distribution fitting technique known as the maximum entropy method. The discussions in the paper substantiate the confident application of the moment-based approach among practitioners. Furthermore, the results from the performance analysis of the maximum entropy method could guide practitioners in selecting a distribution fitting algorithm that best suits their respective systems.

    Original languageEnglish
    Title of host publicationI2MTC 2017 - 2017 IEEE International Instrumentation and Measurement Technology Conference, Proceedings
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    ISBN (Electronic)9781509035960
    Publication statusPublished - 5 Jul 2017
    EventIEEE International Instrumentation and Measurement Technology Conference 2017 - Torino, Italy
    Duration: 22 May 201725 May 2017


    ConferenceIEEE International Instrumentation and Measurement Technology Conference 2017
    Abbreviated titleI2MTC 2017
    Internet address


    • Benchmark distributions
    • Distribution bounds
    • Guide to the expression of uncertainty in measurement (GUM)
    • Maximum entropy
    • Measurement uncertainty
    • Moment problem

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