Investigating the applicability of parallelized straight simulation
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2022-06-20
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en
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Abstract
Straight simulation is an approximate Bayesian inference algorithm and an instance of the
Markov Chain Monte Carlo algorithms. It has been developed to resolve some issues of prior
techniques but ended up showing some problems in other areas itself. As part of this project
the applicability of parallelizing straight simulation will be investigated, since this might enable
a significant performance increase. In particular the influencing properties for poor or decent
accuracy will be explored through exploratory testing. Nonetheless, completely parallelizing
straight simulation generally implies the loss of guarantee to converge to the posterior distribution.
The discussion of the results support this observation in most cases, while describing
under which circumstance a decent approximation is still viable for parallel straight simulation.
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Faculteit der Sociale Wetenschappen