Software for Flexible Bayesian Modeling

Version of 1999-12-06. Copyright (c) 1995, 1996, 1997, 1998, 1999 by Radford M. Neal

Index to documentation for software that implements flexible Bayesian models based on neural networks, Gaussian processes, and mixtures, and that demonstrates various Markov chain Monte Carlo methods.

Introduction, overview, and examples:

Notes on the present release and past releases:

Alphabetical index within directories:

   ........ UTIL .........     ..... MC .....    .... DIST .....   ... BVG ...

   calc         model-spec     mc                dist              bvg
   data-spec    numin          mc-ais            dist-display      bvg-initial
   extract      prior          mc-quantities     dist-est          bvg-mc
   find-min     quantities     mc-spec           dist-gen          bvg-plt
   formula      rand-seed      mc-temp-filter    dist-initial      bvg-spec
   grid         series         mc-temp-sched     dist-mc
   log          xxx-hist       xxx-grad-test     dist-quantities
   log-append   xxx-plt        xxx-mc            dist-spec
   log-copy     xxx-tbl        xxx-stepsizes     dist-stepsizes
   log-last                        
   log-records                      
   log-types                        


   .... NET .....     .... GP .....    .... MIX .....

   net                gp               mix
   net-dvar           gp-cov           mix-cases
   net-display        gp-display       mix-display
   net-eval           gp-eigen         mix-extensions
   net-gd             gp-eval          mix-gen
   net-gen            gp-gen           mix-mc
   net-hist           gp-mc            mix-quantities 
   net-mc             gp-pred          mix-spec
   net-plt            gp-quantities  
   net-pred           gp-spec
   net-quantities
   net-rej 
   net-spec 
   net-tbl 
A more detailed index is given below, with the most important documentation files marked with an asterisk.

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

    formula         Syntax for arithmetic formulas
    calc            Simple calculator program

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

  * 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

  * quantities      Numeric quantities obtainable from log files

  * xxx-plt         Write quantities from log files, suitable for plotting
    xxx-tbl         Write quantities from log files in a tabular form
    xxx-hist        Build a histogram for a quantity using data from log files

  * 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
    mc-ais          Monitor annealed importance sampling (AIS) runs

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

Markov chain sampling for a specified distribution [dist]:

  * dist            Markov chain sampling for a specified distribution
  * dist-spec       Specify a distribution to sample from

    dist-initial    Specify initial state for Markov chain
    dist-stepsizes  Display, evaluate, or set stepsizes used for dynamics
  * dist-mc         Do Markov chain sampling for the specified distribution
    dist-gen        Generate values for state variables from the prior

    dist-display    Print state variables at a specified iteration
  * dist-quantities Quantities defined for a specified distribution

  * dist-est        Estimate the expectation of some function of state

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-initial     Set initial state for sampling from a bivariate Gaussian
    bvg-mc          Do Markov chain simulation for a bivariate Gaussian

    bvg-plt         Get quantities from a bvg log file, suitable to plot

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 net log files, suitable for plotting
    net-tbl         Get quantities from net log files and output as table
    net-hist        Build histogram for quantity obtained from net log files

  * 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