Software WinBugs

Mixed effects models under a Bayesian framework have been widely studied and used with the use of Markov chain Monte Carlo methods (10). These methods have gained particular popularity as complex problems became easily formulated using the WinBUGS software (11). See Congdon (12) for an extensive coverage of topics and examples and implementation in WinBUGS. 

The use of Bayesian methods to conduct network meta-analysis is rapidly growing. For example, recent publications include the Evidence Synthesis Technical Support Documents series found on the website of the Decision Support Unit (DSU) of the National Institute for Health and Care Excellence [27]. The statistical methods used in these documents were primarily Bayesian, and WinBUGS was used as the main software platform for data analysis. The documents can be downloaded from the site http //www. nicedsu.org.uk/Evidence-Synthesis-TSD-series%282391675%29.htm. 

This paper presents a new method for the application of Bayesian theory and technology to product reliability growth during product development phase. The research work mainly focuses on how to determent prior distribution parameters of a new Dirichlet distribution and presents the relevant optimization model and method, finally demonstrate the validity of Bayesian reliability growth model by WinBUGS software. The conclusions as following ... 

Regarding the issue of multidimensional niuner-ical integration of posterior, the paper employs WinBUGS software to establish the reliability growth model based on a new Dirichlet prior distribution, and solves posterior inference of parameters at the same time keeping enough calculation accuracy. 

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