NET-MC: Do Markov chain simulation to sample networks. The net-mc program is the specialization of xxx-mc to the task of sampling from the posterior distribution for a neural network model, or from the prior distribution, if no training set is specified. See xxx-mc.doc for the generic features of this program. The following applications-specific sampling procedures are implemented: sample-hyper Does Gibbs sampling for the hyperparameters controlling the distributions of parameters (weights, etc.). sample-noise Does Gibbs sampling for the noise variances. sample-sigmas Does both sample-hyper and sample-noise. Default stepsizes are set by a complicated heuristic procedure that is described in Appendix A of the thesis. Tempering methods are not currently supported. Copyright (c) 1995 by Radford M. Neal