60 research outputs found
Multi-dimensional Density of States by Multicanonical Monte Carlo
Full text linkMulti-dimensional density of states provides a useful description of complex
frustrated systems. Recent advances in Monte Carlo methods enable efficient
calculation of the density of states and related quantities, which renew the
interest in them. Here we calculate density of states on the plane (energy,
magnetization) for an Ising Model with three-spin interactions on a random
sparse network, which is a system of current interest both in physics of glassy
systems and in the theory of error-correcting codes. Multicanonical Monte Carlo
algorithm is successfully applied, and the shape of densities and its
dependence on the degree of frustration is revealed. Efficiency of
multicanonical Monte Carlo is also discussed with the shape of a projection of
the distribution simulated by the algorithm.Comment: Presented at SPDSA 2004, Hayama, Japa
Posterior Covariance Information Criterion
Full text linkWe introduce an information criterion, PCIC, for predictive evaluation based
on quasi-posterior distributions. It is regarded as a natural generalisation of
the widely applicable information criterion (WAIC) and can be computed via a
single Markov chain Monte Carlo run. PCIC is useful in a variety of predictive
settings that are not well dealt with in WAIC, including weighted likelihood
inference and quasi-Bayesian predictio
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