Index to documentation for software that implements flexible Bayesian models based on neural networks, Gaussian processes, mixtures, and Dirichlet diffusion trees, and that demonstrates various Markov chain Monte Carlo methods.
........ 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-circ dist-quantities log-append xxx-plt xxx-genp dist-spec log-copy xxx-tbl xxx-grad-test dist-stepsizes log-equal xxx-his log-last xxx-mc log-records xxx-stepsizes log-types xxx-wrap .... NET ..... .... GP ..... .... MIX ..... .... DFT .... net gp mix dft net-approx gp-cov mix-cases dft-cases net-dvar gp-display mix-display dft-dendrogram net-display gp-eigen mix-gen dft-display net-eval gp-eval mix-mc dft-gen net-gd gp-gen mix-pred dft-mc net-gen gp-mc mix-quantities dft-pred net-hist gp-pred mix-spec dft-quantities net-mc gp-quantities dft-spec net-plt gp-spec net-pred net-quantities net-rej net-spec net-tblA more detailed index is given below, with the most important documentation files marked with an asterisk.
* 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
* 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-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-genp Do Hamiltonian importance sampling
* 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
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
* 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-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-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
* 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
* 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
* 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