Split Hamiltonian Monte Carlo revisited
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Title
Split Hamiltonian Monte Carlo revisitedDate
2022Publisher
SpringerBibliographic citation
Casas, F., Sanz-Serna, J.M. & Shaw, L. Split Hamiltonian Monte Carlo revisited. Stat Comput 32, 86 (2022). https://doi.org/10.1007/s11222-022-10149-4Type
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info:eu-repo/semantics/publishedVersionAbstract
We study Hamiltonian Monte Carlo (HMC) samplers based on splitting the Hamiltonian H as H0(θ , p)+U1(θ ), where H0 is
quadratic and U1 small. We show that, in general, such samplers suffer from stepsize stability ... [+]
We study Hamiltonian Monte Carlo (HMC) samplers based on splitting the Hamiltonian H as H0(θ , p)+U1(θ ), where H0 is
quadratic and U1 small. We show that, in general, such samplers suffer from stepsize stability restrictions similar to those of
algorithms based on the standard leapfrog integrator. The restrictions may be circumvented by preconditioning the dynamics.
Numerical experiments show that, when the H0(θ , p) + U1(θ ) splitting is combined with preconditioning, it is possible to
construct samplers far more efficient than standard leapfrog HMC. [-]
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Statistics and Computing (2022) 32:86Rights
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