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Amanda Koepke

Amanda Koepke graduated from Texas Tech University in 2008 with a B.A. in Mathematics and Statistics and a B.A. in Psychology. In 2014 she received her Ph.D. in Statistics from the University of Washington. She completed a year-long postdoctoral research fellowship at the Fred Hutchinson Cancer Research Center in Seattle before joining the Statistical Engineering Division at NIST in 2015.

Amanda's current research interests include Bayesian analysis, meta-analysis/interlaboratory studies, and stochastic modeling.


Technical Areas of Research and Consulting:

  • Bayesian analysis
  • Statistical modeling
  • Uncertainty analysis
  • Markov chain Monte Carlo methods, including particle filters and other approximate methods
  • Consensus values




  • 2015 Young Investigator Award from the Statistics in Epidemiology Section of the American Statistical Association.


Channel Sounder Measurement Verification: Conducted Tests

Jeanne T. Quimby, Jeffrey A. Jargon, Rodney W. Leonhardt, Jake D. Rezac, Paul D. Hale, Catherine A. Remley, Amanda A. Koepke, Robert Johnk, chriss Hammerschmidt, Paul Mckenna, Irena Stange, Mike Chang
Channel modeling often provides a basis for the design and deployment of wireless technology. Engineers design systems to operate under certain expected channel

Monte Carlo Sampling Bias in the Microwave Uncertainty Framework

Michael R. Frey, Benjamin F. Jamroz, Amanda A. Koepke, Jake D. Rezac, Dylan F. Williams
The Microwave Uncertainty Framework (MUF) is a software suite created, supported, and made publicly available by the Radio Frequency Division of the U.S
Created June 5, 2018, Updated February 7, 2020