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Efficiency and time-dependent cross correlations in multivariable Monte Carlo updating.

Christopher C J Potter1, Robert H Swendsen2

  • 1Department of Mathematical Sciences, Carnegie-Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 17, 2013
PubMed
Summary

Jointly updating variables in Monte Carlo (MC) algorithms can create misleading correlations, impacting efficiency estimates. Separate variable updates are generally more efficient than global ones, suggesting a need to re-evaluate optimal acceptance ratios.

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