DIST-MC: Do Markov chain sampling for the specified distribution. The dist-mc program samples from the distribution specified with dist-spec (see dist-spec.doc) using a specified series of Markov chain operations (see mc-spec.doc). All the standard Markov chain operations are supported. The default stepsizes are all one. These stepsizes may be multiplied by a stepsize adjustment specified by the user, in the usual way. For distributions specified by a single energy function, the inverse temperature used in tempering methods may be interpreted in two ways, as appropriate for traditional tempering method (-zero-temper) or for annealed importance sampling. See dist-spec.doc for details. For Bayesian posterior distributions, the inverse temperature is used to multiply the log likelihood terms (see dist-spec.doc). An inverse temperature of zero therefore gives the prior distribution. Dist-mc knows how to sample from this prior distribution if it has a simple form (see dist-spec.doc). Otherwise, if annealed importance sampling is to be used, the -read-prior option must have been given to dist-spec, which tells dist-mc to obtain points drawn from the prior from an external source. It does this by reading them from standard input, as a free-form list of numbers in standard text form, with the the state variables being read in the order: u0, ..., u9, u, v0, ..., v9, v, w0, ..., w9, w, x0, ..., x9, x, y0, ..., y9, y, z0, ..., z9, z. There are no "application specific" operations implemented by dist-mc. For details regarding program arguments, see the generic documentation in xxx-mc.doc. Copyright (c) 1995-2004 by Radford M. Neal