Journal article
Rapid Bayesian inference for expensive stochastic models
- Abstract:
-
Almost all fields of science rely upon statistical inference to estimate unknown parameters in theoretical and computational models. While the performance of modern computer hardware continues to grow, the computational requirements for the simulation of models are growing even faster. This is largely due to the increase in model complexity, often including stochastic dynamics, that is necessary to describe and characterize phenomena observed using modern, high resolution, experimental techni...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Funding
+ Biotechnology and Biological Sciences Research Council
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Grant:
BB/R000816/1
Funder identifier:
http://dx.doi.org/10.13039/501100000268
Bibliographic Details
- Publisher:
- Taylor and Francis Publisher's website
- Journal:
- Journal of Computational and Graphical Statistics Journal website
- Volume:
- 31
- Issue:
- 2
- Pages:
- 512-528
- Publication date:
- 2021-11-04
- Acceptance date:
- 2021-06-29
- DOI:
- EISSN:
-
1537-2715
- ISSN:
-
1061-8600
Item Description
Terms of use
- Copyright holder:
- American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America
- Copyright date:
- 2021
- Rights statement:
- © 2021 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America
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