Software for Flexible Bayesian Modeling

Version of 2022-04-21. Copyright (c) 1995-2022 by Radford M. Neal

Index to documentation on software for various Markov chain Monte Carlo methods and their use for various flexible Bayesian models as well as molecular simulation.

Introduction, overview, and examples:

Notes on the present release and past releases:

Alphabetical index within directories:

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

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


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

   net                gp               mix               dft
   net-approx         gp-cov           mix-cases         dft-cases
   net-config         gp-dgen          mix-display       dft-dendrogram
   net-config-check   gp-display       mix-gen           dft-display
   net-dvar           gp-eigen         mix-mc            dft-gen
   net-display        gp-eval          mix-pred          dft-mc
   net-eval           gp-gen           mix-quantities    dft-pred 
   net-gd             gp-mc            mix-spec          dft-quantities 
   net-gen            gp-pred                            dft-spec
   net-hist           gp-quantities
   net-mc             gp-spec
   net-plt
   net-pred
   net-quantities
   net-rej 
   net-spec 
   net-tbl 


   .... SRC ....      .... MOL .....  

   src                mol
   src-dgen           mol-display
   src-display        mol-mc
   src-gen            mol-quantities
   src-initial        mol-spec
   src-intensity
   src-mc
   src-pred
   src-quantities
   src-spec
   det-spec
   flow-spec
 
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
    log-equal       Check if records in log files match

    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
  * mean            Compute means with standard errors

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 a Markov chain simulation
  * xxx-circ        Do a circularly-coupled simulation
  * xxx-wrap        Create wrapped-around chain from existing simulation run

  * 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-mc-test     Do a joint distribution test of MCMC correctness
    xxx-grad-test   Test the correctness of the energy gradient computations
    xxx-stepsizes   Display and evaluate stepsizes used for dynamics
    xxx-genp        Generate random momentum variables

    xxx-his         Do Hamiltonian importance sampling

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-dgen       Generate values for target variables using given parameters

    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-config      Specify weight configuration for a layer's connections

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

  * net-display     Print network parameters and/or hyperparameters
    net-config-check  Check/display a network configuration specification

  * 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-dgen         Generate values for target variables given latent values

  * 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-pred        Make predictions for tests cases using mixture models
    mix-cases       Generate cases from a mixture model

Bayesian inference for Dirichlet diffusion tree models [dft]:

  * dft             Bayesian inference for diffusion tree models
  * dft-spec        Specify a diffusion tree model, or display existing spec

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

  * dft-display     Print diffusion tree model parameters, hyperparameters, etc.
    dft-dendrogram  Create Postscript representation of a dendrogram of a tree
  * dft-quantities  Quantities from log files relating to diffusion tree models

  * dft-pred        Make predictions for test cases using diffusion tree model

    dft-cases       Generate cases from a diffusion tree model

Bayesian inference for locations of sources of atmospheric contamination [src]:

  * src             Programs for inferring source locations from detector readings
  * src-spec        Specify priors of the number and location of sources
  * det-spec        Specify detector noise model
  * flow-spec       Specify flow model

  * src-mc          Do Markov chain sampling for source location models
    src-initial     Set initial values for parameters of a source location model
    src-gen         Generate randomly from the prior for a source location model
    src-dgen        Randomly generate detector measurements given source parameters

  * src-display     Print the parameters of a source location model
  * src-quantities  Quantities from log files relating to source models

  * src-pred        Make predictions for measurements in test cases
  * src-intensity   Make predictions for source intensity in grid cells.

Molecular simulation with Lennard-Jones potential [mol]:

  * mol             Molecular simulation with Lennard-Jones potential
  * mol-spec        Specify a molecular system

  * mol-mc          Do Markov chain sampling for a molecular system

    mol-display     Print state of molecular system
  * mol-quantities  Quantities from log files relating to molecular systems