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• W2963730944 abstract "We present a new approach to sample from generic binary distributions, based on an exact Hamiltonian Monte Carlo algorithm applied to a piecewise continuous augmentation of the binary distribution of interest. An extension of this idea to distributions over mixtures of binary and possibly-truncated Gaussian or exponential variables allows us to sample from posteriors of linear and probit regression models with spike-and-slab priors and truncated parameters. We illustrate the advantages of these algorithms in several examples in which they outperform the Metropolis or Gibbs samplers." @default.
• W2963730944 created "2019-07-30" @default.
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• W2963730944 date "2013-12-05" @default.
• W2963730944 modified "2023-09-24" @default.
• W2963730944 title "Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions" @default.
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