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    • Optimal Bayesian Experimental Design

    Metadata Updated: September 30, 2025

    Python module "optbayesexpt" uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given a parametric model - analogous to a fitting function - Bayesian inference uses each measurement "data point" to refine model parameters. Using this information, the software suggests measurement settings that are likely to efficiently reduce uncertainties. A TCP socket interface allows the software to be used from experimental control software written in other programming languages. Code is developed in python and shared via GitHub's USNISTGOV organization.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    References

    https://doi.org/10.18434/M32090

    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date September 30, 2025
    Data Update Frequency irregular

    Metadata Source

    Harvested from Commerce Non Spatial Data.json Harvest Source

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date September 30, 2025
    Publisher National Institute of Standards and Technology
    Maintainer
    Identifier 8E5FC500E0A4777CE0532457068151792090
    Data First Published 2020-04-13
    Language en
    Data Last Modified 2019-07-22 00:00:00
    Category Mathematics and Statistics:Experiment design, Mathematics and Statistics:Numerical methods and software, Physics:Magnetics
    Public Access Level public
    Data Update Frequency irregular
    Bureau Code 006:55
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 2dbb489c-c9af-42cb-a695-3ee9ebc11ded
    Harvest Source Id bce99b55-29c1-47be-b214-b8e71e9180b1
    Harvest Source Title Commerce Non Spatial Data.json Harvest Source
    Homepage URL https://data.nist.gov/od/id/8E5FC500E0A4777CE0532457068151792090
    License https://www.nist.gov/open/license
    Program Code 006:045
    Related Documents https://doi.org/10.18434/M32090
    Source Datajson Identifier True
    Source Hash 7549b87895b1625b30aca32aa3cafeacda9af198c26f534e94fe49a27db126f5
    Source Schema Version 1.1

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