    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