    NET-REJ:  Generate networks from the posterior by rejection sampling.

    Net-rej generates networks from the posterior distribution given
    training data using the architecture, priors, and data specifications
    obtained from the given log file, to which the generated networks are
    also written.  The rejection sampling procedure used is exceedingly
    inefficient, and is useful only in providing a check (in very small
    examples) on whether the Markov chain methods are working properly.

    Usage:

        net-rej log-file max-index [ rejection-limit ]

    The networks with indexes from zero up to the indicated index are
    generated, as long as the number of rejections does not exceed the
    limit (default is infinity).  If the log file already contains
    networks with some of these indexes, only the networks with indexes
    greater than the last one in the log file are generated.

    Networks are generated from the posterior by sampling from the prior
    (with an adjustment for noise variances in the case of real-valued
    outputs), and then rejecting some generated states based on the
    likelihood.

    The observed acceptance rate is displayed on standard error at the end
    of the program.

    Two records are written to the log file for every network generated -
    an 'S' record containing the hyperparameters ('sigma' values), and a
    'W' record containing the parameters (weights, biases, and offsets).
    An 'r' record recording the random number generator state is written
    as well.

                Copyright (c) 1995-2003 by Radford M. Neal