Closure to “Transitional Markov Chain Monte Carlo: Observations and Improvements” by Wolfgang Betz, Iason Papaioannou, and Daniel Straub
This article is a reply.
VIEW THE ORIGINAL ARTICLEAuthors: Wolfgang Betz [email protected], Iason Papaioannou, Ph.D. [email protected], and Daniel Straub, Ph.D. [email protected]Author Affiliations
Publication: Journal of Engineering Mechanics
Volume 143, Issue 9
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References
Ching, J., and Chen, Y.-C. (2007). “Transitional Markov chain Monte Carlo method for Bayesian model updating, model class selection, and model averaging.” J. Eng. Mech., 816–832.
Gelman, A., Roberts, G., and Gilks, W. (1996). “Efficient metropolis jumping rules.” Bayesian Stat., 5, 599–607.
MATLAB [Computer software]. MathWorks, Natick, MA.
Roberts, G. O., Gelman, A., and Gilks, W. R. (1997). “Weak convergence and optimal scaling of random walk metropolis algorithms.” Ann. Appl. Probab., 7(1), 110–120.
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©2017 American Society of Civil Engineers.
History
Received: Sep 4, 2016
Accepted: Feb 14, 2017
Published online: Jun 13, 2017
Published in print: Sep 1, 2017
Discussion open until: Nov 13, 2017
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Engineering Risk Analysis Group, Technische Universität München, 80333 München, Germany (corresponding author). E-mail: [email protected]
Engineering Risk Analysis Group, Technische Universität München, 80333 München, Germany. E-mail: [email protected]
Professor, Engineering Risk Analysis Group, Technische Universität München, 80333 München, Germany. E-mail: [email protected]
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