Optimal Bayesian Experimental Design Version 1.0.1

Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an 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.

Data and Resources

Documentation for Optimal Bayesian Experimental Design
Explore
- More information
- Go to resource
DOI Access for Optimal Bayesian Experimental...
Explore
- More information
- Go to resource
Optimal Bayesian Experimental Design v. 1.0.1Python source code, documentation in Jupyter notebook, markdown and rst formats
Python module 'optbayesexpt' uses optimal Bayesian experimental design...
Explore
- More information
- Go to resource

Additional Info

Field	Value
Maintainer	Robert D. McMichael
Last Updated	March 5, 2021, 07:22 (EST)
Created	March 5, 2021, 07:22 (EST)
Identifier	ark:/88434/mds2-2230
Language	{en}
Modified	2020-04-01 00:00:00
Theme	{Physics:Magnetics}
accessLevel	public
accrualPeriodicity	irregular
bureauCode	{006:55}
catalog_@context	https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_conformsTo	https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy	https://project-open-data.cio.gov/v1.1/schema/catalog.json
encoding	utf8
harvest_url	http://catalog.data.gov/dataset/08ab92ad-997e-4f29-9a4d-4c0c2d2a3f5d
landingPage	https://data.nist.gov/od/id/mds2-2230
license	https://www.nist.gov/open/license
programCode	{006:045}
publisher	National Institute of Standards and Technology
resource-type	Dataset
source_datajson_identifier	true
source_hash	365192c2affcfa5648e2994f18205591535b19eb
source_schema_version	1.1