This paper develops a methodology for robust Bayesian inference through the use of disparities. Metrics such as Hellinger distance and negative exponential disparity have a long history in robust estimation in frequentist inference. We demonstrate that an equivalent robustification may be made in Bayesian inference by substituting an appropriately scaled disparity for the log likelihood to whic...

We describe a Bayesian Reasoning Framework (BRF) that supports business rule operations for on-line information systems. BRF comprises a three-layer environment with business information systems at the top, a middle-ware Bayesian reasoning server, and a Bayesian reasoning engine at the bottom. The top and middle-ware layers communicate via SOAP/XML protocol, while the middle-ware and bottom lay...

This paper has been written in order to apply Bayesian network modelling to a maintenance and inspection department. The primary aim of this paper is to establish and model the various parameters responsible for the failure rate of a system, using Bayesian network modelling, in order to apply it to a delay-time analysis study. The use of Bayesian network modelling allows certain influencing eve...

BACKGROUND Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia....

• A novel evaluation methodology combining Markov model and dynamic Bayesian networks is developed. The external disaster established by mapping from actual physical models of influencing factors. Power supply control systems subsea blowout preventers demonstrates the application methodology. Many resilience methods were proposed to assess system under influence specific, constant disasters, th...

We consider situations in Bayesian analysis where the prior is indexed by a hyperparameter taking on a continuum of values. We distinguish some arbitrary value of the hyperparameter, and consider the problem of estimating the Bayes factor for the model indexed by the hyperparameter vs. the model specified by the distinguished point, as the hyperparameter varies. We assume that we have Markov ch...

This article describes a Bayesian semiparametric approach for assessing agreement between two methods for measuring a continuous variable using tolerance bands. A tolerance band quantifies the extent of agreement in methods as a function of a covariate by estimating the range of their differences in a specified large proportion of population. The mean function of differences is modelled using a...