The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Differential Evolution Markov Chain with snooker updater and fewer chains
Open accessAbstract
Differential Evolution Markov Chain (DE-MC) is an adaptive MCMC algorithm, in which multiple chains are run in parallel. Standard DE-MC requires at least N=2d chains to be run in parallel, where d is the dimensionality of the posterior. This paper extends DE-MC with a snooker updater and shows by simulation and real examples that DE-MC can work for d up to 50–100 with fewer parallel chains (e.g. N=3) by exploiting information from their past by generating jumps from differences of pairs of past states. This approach extends the practical applicability of DE-MC and is shown to be about 5–26 times more efficient than the optimal Normal random walk Metropolis sampler for the 97.5% point of a variable from a 25–50 dimensional Student t 3 distribution. In a nonlinear mixed effects model example the approach outperformed a block-updater geared to the specific features of the model.
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Storn, R., & Price, K. (1997) · Journal of Global Optimization · doi:10.1023/a:1008202821328 · Cited by 29,569
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Mixed-Effects Models in S and S-PLUS
(2001) · Technometrics · doi:10.1198/tech.2001.s574 · Cited by 9,278
Mixed-Effects Models in S and S-PLUS
(2000) · Statistics and Computing · doi:10.1007/b98882 · Cited by 930
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?
Vrugt, J. A., ter Braak, C. J. F., Gupta, H. V., & Robinson, B. A. (2009) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-008-0274-y · Cited by 455
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Cited by
Veitch, J., Raymond, V., Farr, B., Farr, W., Graff, P., Vitale, S., Aylott, B., Blackburn, K., Christensen, N., Coughlin, M., et al. (2015) · Physical Review D · doi:10.1103/physrevd.91.042003 · Cited by 958
Vrugt, J. A. (2016) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2015.08.013 · Cited by 851
Self-citationSchoups, G., & Vrugt, J. A. (2010) · Water Resources Research · doi:10.1029/2009wr008933 · Cited by 565
Self-citationNon-stationary extreme value analysis in a changing climate
Cheng, L., AghaKouchak, A., Gilleland, E., & Katz, R. W. (2014) · Climatic Change · doi:10.1007/s10584-014-1254-5 · Cited by 537
von Toussaint, U. (2011) · Reviews of Modern Physics · doi:10.1103/revmodphys.83.943 · Cited by 422
Metadata
- Authors
- ter Braak, C. J. F., & Vrugt, J. A.
- Venue
- Statistics and Computing
- Published
- 2008-10-21
- Volume
- 18
- Issue
- 4
- Pages
- 435-446
- ISSN
- 0960-3174 (ISSN-L)
- 1573-1375
- OpenAlex
- W2144661611
- Cited by
- 591
- References
- 5
- FWCI
- 6.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- ter Braak, C. J. F., & Vrugt, J. A. (2008). Differential Evolution Markov Chain with snooker updater and fewer chains. Statistics and Computing. https://doi.org/10.1007/s11222-008-9104-9
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