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An exact auxiliary variable Gibbs sampler for a class of diffusions

Abstract:

Stochastic differential equations (SDEs) or diffusions are continuous-valued continuous-time stochastic processes widely used in the applied and mathematical sciences. Simulating paths from these processes is usually an intractable problem, and typically involves time-discretization approximations. We propose an exact Markov chain Monte Carlo sampling algorithm that involves no such time-discretization error. Our sampler is applicable to the problem of prior simulation from an SDE, posterior ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1080/10618600.2020.1816177

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
ORCID:
0000-0001-5365-6933
Publisher:
Taylor and Francis
Journal:
Journal of Computational and Graphical Statistics More from this journal
Volume:
30
Issue:
2
Pages:
297-311
Publication date:
2020-10-09
Acceptance date:
2020-08-03
DOI:
EISSN:
1537-2715
ISSN:
1061-8600
Language:
English
Keywords:
Pubs id:
991927
Local pid:
pubs:991927
Deposit date:
2020-09-17

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