Rejection Approximate Bayesian Computation
Rejection Approximate Bayesian Computation is a likelihood-free inference method that belongs to the class of Approximate Bayesian Computation techniques, distinguished by its use of direct rejection sampling to accept parameter proposals only when simulated data fall within a predefined tolerance threshold of the observed data.
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1.9K
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71
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49
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2017–2026
8
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ABCtoolbox: a versatile toolkit for approximate Bayesian computations
Daniel Wegmann, Christoph Leuenberger, Samuel Neuenschwander et al. · BMC Bioinformatics · 2010 · 450 citations · Full text
ABC-SysBio—approximate Bayesian computation in Python with GPU support
Juliane Liepe, C. Barnes, Erika Cule et al. · Bioinformatics · 2010 · 143 citations · Full text
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Imperial College London
London, United Kingdom
3 h-index
19 publications
2.4K citations

Commonwealth Scientific and Industrial Research Organisation
Canberra, Australia
2 h-index
2 publications
90 citations

The University of Melbourne
Melbourne, Australia
2 h-index
3 publications
54 citations
University of Reading
Reading, United Kingdom
2 h-index
4 publications
387 citations
University of Bern
Bern, Switzerland
2 h-index
3 publications
1.2K citations

UNSW Sydney
Sydney, Australia
2 h-index
6 publications
270 citations
Google (United States)
Mountain View, United States
1 h-index
1 publications
44 citations
University of Wyoming
Laramie, United States
1 h-index
1 publications
81 citations
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3 publications · 196 citations
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2 publications · 98 citations
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SAGMB · 2 publications · 81 citations
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1 publications · 273 citations
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1 publications · 23 citations
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