GUIDE TO FURTHER DOCUMENTATION

The overview and examples above are intended just to get you started.
To use the software to do real work, you will probably need to refer
to the detailed documentation on the commands (and common aspects of
commands) contained in the files ending with ".doc" which are found in
the various sub-directories, and also all collected in the 'doc'
directory.  For quick reference, all commands print a brief summary of
the command syntax when they are invoked with no arguments.

In the syntax descriptions used, the characters "[" and "]" enclose
parts of the command that are optional, "{" and "}" enclose optional
parts that can be repeated, and "|" separates alternatives.  Except
for the command name (or other obvious keywords), the words in the
syntax descriptions are descriptive of what is to be entered, except
that words in quotes are to be entered literally (without the quotes).

The ".doc" files present in the various directories are listed below,
with the more important files marked by "*".  Programs listed as
"xxx-something" are generic, with "xxx" being replaced by the name of
an application (eg, "net", "gp", or "mix").  In some cases, further
documentation is available under the specific name.

The file index.html is a hypertext index to this documenation.  It can
be accessed using a Web browser (eg, xmosaic or netscape), by a
command such as

    > xmosaic index.html

or by opening index.html as a local file in a browser that you are
already running. The index.html file must reside in the 'doc'
directory for this software.  One needn't start the browser from this
directory, however, provided one uses a full path name to identify
index.html.  The files accessed this way are .html files derived from
the .doc files.  The content is identical, except that references to
other .doc files have been converted into hypertext links that you can
follow with the browser.

All the introductory documentation (including this) is collected into
the 'manual' file.  You can print all the documentation by going to
the main directory for this software and issuing a command such as

  lpr doc/manual util/*.doc mc/*.doc net/*.doc gp/*.doc mix/*.doc doc/rel*
 
(or using whatever command other than 'lpr' you use to print text files).


Generic utility programs [util]:

  * log             Facilities for handling log files
    log-types       Types of log file records used by various programs

    log-copy        Copy part of a log file to a new log file
    log-append      Append records from one log file to the end of another
    log-last        Display the index of the last record in a log file
    log-records     List all records in a log file  

  * data-spec       Specify data sets for training and testing
  * numin           Facilities for input of numeric data
    numin-test      Test numeric input module

  * model-spec      Specify model for targets
  * prior           Meaning and syntax of prior specifications

    find-min        Find entry with minimum value (for cross validation)

    grid            Output a grid of points  
    extract         Extract items at random from a data file 

  * rand-seed       Specify a random number seed  
    rand-test       Test random number generators

  * quantities      Numeric quantities obtainable from log files

  * xxx-plt         Write quantities from a log file, suitable for plotting
    xxx-hist        Build a histogram for a quantity obtained from a log file

  * series          Analyse stationary time series data


Markov chain Monte Carlo facilities [mc]:

  * mc              Programs and modules supporting Markov chain Monte Carlo 
  * mc-spec         Specify how to do the Markov chain simulation
  * xxx-mc          Run Markov chain simulation

  * mc-quantities   Quantities from log files relating to Monte Carlo 

    mc-temp-sched   Specify temperature schedule for tempering methods
    mc-temp-filter  Copy only iterations at a given temperature

    xxx-grad-test   Test the correctness of the energy gradient computations
    xxx-stepsizes   Display and evaluate stepsizes used for dynamics


Bayesian neural networks [net]:

  * net             Bayesian inference for neural networks using MCMC
  * net-spec        Create a new network, or display existing specifications 

  * net-mc          Do Markov chain simulation to sample networks
  * net-gen         Generate networks from the prior, or with fixed values  
    net-gd          Train a network by gradient descent in the error

  * net-display     Print network parameters and/or hyperparameters

  * net-quantities  Quantities from log files relating to networks
  * net-plt         Get quantities from a net log file, suitable for plotting
    net-hist        Build histogram for quantity obtained from a net log file

  * net-pred        Make predictions for test cases

    net-eval        Evaluate network functions over a grid  
    net-dvar        Find the variance of a difference in function values

    net-rej         Generate networks from the posterior by rejection sampling


Gaussian process models [gp]:

  * gp              Bayesian modelling using Gaussian processes
  * gp-spec         Specify a Gaussian process model, or display existing spec

  * gp-mc           Use Markov chain to sample Gaussian process hyperparameters
  * gp-gen          Generate GP hyperparameters randomly, or fix them

  * gp-display      Print Gaussian process hyperparameters & other information
  * gp-quantities   Quantities from log files relating to Gaussian processes

  * gp-pred         Make predictions for test cases using Gaussian process
    gp-eval         Evaluate function drawn from a Gaussian process over a grid

    gp-cov          Print covariance matrix for a Gaussian process 
    gp-eigen        Find eigenvalues/vectors of covariance matrix


Bayesian inference for mixture models [mix]:

  * mix             Bayesian inference for mixture models
  * mix-spec        Specify a mixture model, or display existing spec

  * mix-mc          Use Markov chain to do sampling for a mixture model
  * mix-gen         Generate hyperparameters randomly, or fix them

  * mix-display     Print mixture model parameters, hyperparameters, etc.
  * mix-quantities  Quantities from log files relating to mixture models

    mix-cases       Generate cases from a mixture model

    mix-extensions  Possible extensions to the mixture modeling software


Markov chain sampling for a bivariate Gaussian [bvg]:

    bvg             Demo of Markov chain sampling from a bivariate Gaussian
    bvg-spec        Specify a bivariate Gaussian distribution to sample from
    bvg-mc          Do Markov chain simulation for a bivariate Gaussian
    bvg-plt         Get quantities from a bvg log file, suitable to plot