Software for Flexible Bayesian Models Based on Neural Networks and Gaussian Processes

Version of 1997-01-18. Copyright (c) 1995, 1996, 1997 by Radford M. Neal

This is an index to documenation for software implementing flexible Bayesian models based on neural networks and Gaussian processes, implemented using Markov chain Monte Carlo methods.

Introduction, overview, and examples:

Notes on the present release and past releases:

Alphabetical index within directories:

     UTIL              MC              NET              GP           BVG

   data-spec      mc                net              gp            bvg
   extract        mc-quantities     net-dvar         gp-display    bvg-plt
   grid           mc-spec           net-display      gp-eval       bvg-mc
   log            mc-temp-filter    net-eval         gp-gen        bvg-spec
   log-copy       mc-temp-sched     net-gen          gp-mc
   log-last       xxx-grad-test     net-hist         gp-pred
   log-records    xxx-mc            net-mc           gp-quantities
   log-types      xxx-stepsizes     net-plt          gp-spec
   model-spec                       net-pred
   numin                            net-quantities
   prior                            net-rej
   quantities                       net-spec
A more detailed index is given below. Note that documentation on some programs used only to test the software is not included in either index. The most important documentation files are marked below 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-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

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

    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 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-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

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