Optimal Bayesian Experimental Design Version 1.0.1
收藏DataCite Commons2020-07-09 更新2025-04-16 收录
下载链接：
https://data.nist.gov/od/id/mds2-2230
下载链接
链接失效反馈官方服务：
资源简介：
Python module "optbayesexpt" version 1.0.1 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.
提供机构：
National Institute of Standards and Technology
创建时间：
2020-07-09
