BACKGROUND The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be chall...

Hierarchical modeling is often used a tool which, as an interdisciplinary effort, combines the estimation technique and data mining techniques to model reliability systems. The reliability of the model is measured in terms of how much sufficiently accurate model is over the entire input range and the level of confidence in predictions. WinBUGS is Windows based software which provides researcher...

This paper deals with Bayesian inferences of animal models using Gibbs sampling. First, we suggest a general and efficient method for updating additive genetic effects, in which the computational cost is independent of the pedigree depth and increases linearly only with the size of the pedigree. Second, we show how this approach can be used to draw inferences from a wide range of animal models ...

We would like to acknowledge the help of Alec Gorjestani and Arvind Menon of the Intelligent Vehicle Laboratory who built, installed, and maintained the infrastructure data collection system. We would also like to acknowledge the help of Gary Davis of the Civil Engineering Department for assistance with the use of the WinBUGS software.

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1 Why Bayesian analysis using MCMC is good for you 1. Has a very solid decision-theoretical framework 2. It is intuitive: a. Combines the prior distribution (prior beliefs and/or experience) with the likelihood (experiment) to obtain the posterior distribution (accumulated information). b. In this context knowledge is equivalent to distribution and knowledge precision can be quantified by the p...

Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This paper implements MCMC methods for Bayesian analysis of stochastic frontier models using the WinBUGS package, a freely available software. General code for cross-sectional and panel data are presented and various ways of summarizing posterior inference are discussed. Several examples illustrate that ...

Myelodysplastic syndrome (MDS), sometimes referred to as pre-leukemia or smoldering leukemia, is a group of diseases usually characterized by failure of the bone marrow to produce enough normal blood cells. In about one-third of patients, the disease transforms into acute leukemia. In high-risk MDS, the bone marrow contains too many immature blood cells known as blasts. Patients with high-risk ...

This paper considers the use of Dirichlet process priors in the statistical analysis of network data. Dirichlet process priors have the advantage of avoiding the parametric specification for distributions which are rarely known and for facilitating a clustering effect which is often applicable to network nodes. The approach is highlighted on two network models and is conveniently implemented us...