We propose a general method for distributed Bayesian model choice, using the marginal likelihood, where data set is split in non-overlapping subsets. These subsets are only accessed locally by individual workers and no shared between workers. approximate evidence full through Monte Carlo sampling from posterior on every subset generating per subset. The results combined novel approach which cor...

E Sistent financial pressures within the Department of Defense have sparked increasing interest in the promise of software reuse as a mechanism to achieve greater efficiency in developing and applying models and simulations to support the systems acquisition process. A perpetual obstacle to the widespread proliferation of reusable software code within 000 is that most existing, older-technology...