    DFT-CASES:  Generate cases from a Dirichlet diffusion tree model.

    Dft-cases produces a data file containing the target values for cases
    generated from a diffusion tree model.  The diffusion tree(s)
    underlying these cases may optionally be displayed as well.

    Usage:

        dft-cases [ -# ] [ -b ] [ -h ] [ -p ] [ -l ] [ -t ] [ -g ] [ -n | -N ]
          log-file index output-file n-cases [ random-seed ] [ new-log-file ]

    Values for the targets in n-cases cases are generated and stored in
    the specified output file, one per line, overwriting any data it
    previously contained.  If no training data has been specified, the
    generated cases will come from the prior distribution conditional on
    the overall hyperparameters and diffusion tree parameters stored in
    the log file under the specified index.  If training data has been
    supplied, the cases will be generated from the posterior distribution
    given the training data, as represented by the hyperparameters,
    parameters, latent vectors, and diffusion trees(s) for training cases
    that are stored under that index.

    Including a flag of the form -#, where # is a digit from 1 up to the
    number of trees in the model, causes the data written to output-file
    to be the values generated at the terminal nodes for that tree, rather
    than the final values for observable variables.  This allows one to
    examine the contributions of the different trees, since running
    dft-cases more than once with different values for this option, or
    without it, but with other arguments such as the random number seed
    the same, will display components of the same randomly-generated data.

    If one or more other flags are specified, the overall hyperparameters,
    diffusion tree parameters, latent vectors, tree structures, or node
    descriptions will be displayed on standard output, in the format
    documented in dft-display.doc, with the newly generated cases
    following the training cases (if any).  By default, none of this
    information is displayed.  When -l or -N is specified, values for
    latent vectors or node locations are displayed even if they are not
    stored in the log file - they are randomly generated if necessary
    (assuming that this is possible for the model being used).

    The random number seed used for generating the cases may be specified
    at the end of the command line.  If it is omitted, index is used as
    the seed.

    If the final new-log-file argument is present, records of the overall
    hyperparameters, diffusion tree parameters, latent vectors, tree
    structures, and node locations for both the original cases and the
    newly-generated cases will be appended to the log file with this name,
    with an index one greater than the index of the current last record.
    This log file should already contain model and data specifications,
    which must be compatible with the records written (though this is not
    checked).  This facility allows a new chain to be run starting from
    the generated state, which is useful for testing.

                Copyright (c) 1995-2004 by Radford M. Neal