Milestones of the Bayesian Metrology Project

• Complete publication on a Bayesian model for interlaboratory comparisons.
• Explore the relationship between the ISO uncertainty procedure and Bayesian statistics.
• Present review of Bayesian statistics to NIST staff.
• Research Bayesian methods for incorporating boundary information in image analysis and other signals with boundaries.

• Research theory and methodology for Bayesian hierachial models with different types of prior distributions.
• Acquire BUGS (software for Bayesian computations using Gibbs sampling).
• Use BUGS to for Bayesian analyses of NIST data.
• Compare different types predictions in the Bayesian and frequentist frameworks

• Apply hierarchical Bayes model to NIST examples, e.g., the Interlaboratory Proficiency Study.
• Formulate Bayesian models for SRM data, for calibration data, part inspection plans.
• Investigate Bayesian sample size calculations.
• Construct optimal Bayesian designs for calibrations and for prototypical interlaboratory comparison experiments.

• Develop and incorporate Bayesian methods that can become standard techniques for physical science and engineering applications and for dealing with typical NIST problems such as
  • quantifying uncertainty
  • calibration
  • SRM certification
  • Key Comparisons
• Develop tools and techniques for assessing the performance of Bayesian methodologies and software products.
• Define analyses for canonical applications and continue to implement Bayesian methodology as web-product in parallel to NIST/SEMATECH Engineering Statistics HANDBOOK.

• Develop or implement graphical representations of Bayesian hierarchical models.
• Implement Bayesian methodology and incorporate into standard NIST statistical practices.

Date created: 8/28/2001
Last updated: 8/28/2001
Please email comments on this WWW page to sedwww@nist.gov.