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.
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 rand-seed series xxx-hist xxx-pltA 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.
* 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
* 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
* 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
* 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
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