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Bayesian measures of model complexity and fit
The posterior mean deviance is suggested as a Bayesian measure of fit or adequacy, and the contributions of individual observations to the fit and complexity can give rise to a diagnostic plot of deviance residuals against leverages.
WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility
How and why various modern computing concepts, such as object-orientation and run-time linking, feature in the software's design are discussed and how the framework may be extended.
Local computations with probabilities on graphical structures and their application to expert systems
The BUGS project: Evolution, critique and future directions
- David J. Lunn, D. Spiegelhalter, Andrew Thomas, N. Best
- Political ScienceStatistics in medicine
- 10 November 2009
A balanced critical appraisal of the BUGS software is provided, highlighting how various ideas have led to unprecedented flexibility while at the same time producing negative side effects.
Machine Learning, Neural and Statistical Classification
Survey of previous comparisons and theoretical work descriptions of methods dataset descriptions criteria for comparison and methodology (including validation) empirical results machine learning on…
Probabilistic Networks and Expert Systems
- R. Cowell, A. Dawid, S. Lauritzen, D. Spiegelhalter
- Computer ScienceInformation Science and Statistics
- 1 August 1999
This book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms of probabilistic expert systems, emphasizing those cases in which exact answers are obtainable.
Markov Chain Monte Carlo in Practice
The Markov Chain Monte Carlo Implementation Results Summary and Discussion MEDICAL MONITORING Introduction Modelling Medical Monitoring Computing Posterior Distributions Forecasting Model Criticism Illustrative Application Discussion MCMC for NONLINEAR HIERARCHICAL MODELS.
The BUGS Book: A Practical Introduction to Bayesian Analysis
Introduction: Probability and Parameters Probability Probability distributions Calculating properties of probability distributions Monte Carlo integration Monte Carlo Simulations Using BUGS…
A Language and Program for Complex Bayesian Modelling
This work describes some general purpose software that is currently developing for implementing Gibbs sampling: BUGS (Bayesian inference using Gibbs sampling), written in Modula-2 and runs under both DOS and UNIX.