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OpenBUGS

OpenBUGS is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand OpenBUGS rather than just read about it. In short: OpenBUGS is a software application for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. OpenBUGS is the open source variant of WinBUGS (Bayesian inference Using Gibbs Sampling).

Key takeaways

  • OpenBUGS belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect OpenBUGS to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of OpenBUGS from memory before moving on to harder problems.

Reference excerpt

OpenBUGS is a software application for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. OpenBUGS is the open source variant of WinBUGS (Bayesian inference Using Gibbs Sampling). It runs under Microsoft Windows and Linux, as well as from inside the R statistical package. Versions from v3.0.7 onwards have been designed to be at least as efficient and reliable as WinBUGS over a range of test applications.

Differences from WinBUGS In addition to the different licence and greater range of operating systems, a fundamental difference between OpenBUGS and WinBUGS is the way in which the expert system selects the updating algorithm to use for the class of full conditional distribution of each node. While WinBUGS defines one algorithm for each possible class, there is no limit to the number of algorithms that OpenBUGS can use, allowing greater flexibility and extensibility. The user can select the updater to be used for each node after compilation. Further differences are detailed on the OpenBUGS website.

Programming language The source code of OpenBUGS is written in the Component Pascal programming language and is dependent on the Component Pascal libraries provided by Oberon Microsystems as part of the Blackbox Component Framework. The development tools are available as open source. Binaries of the current version of OpenBUGS are available for Microsoft Windows, and the previous version for Linux, it can also run under WINE for Linux. Installation problems, development and usage questions are discussed at the OpenBUGS Bulletin Board. Attempts to port OpenBUGS to Java with the Gardens Point Component Pascal were given up in favor of a new portable implementation called JAGS. The BUGS language is the language that specifies the model code. It is parsed by OpenBUGS, which then creates an executable (compiled code) that generates a sample from the posterior distribution when run. OpenBUGS was designed to run together with S-Plus and the BUGS language is similar to the S programming language. OpenBUGS works well together with R; the R2OpenBUGS or BRugs packages provides some interoperability, and R modules help further analyses.

References

External links OpenBugs at the University of Cambridge Since 2021 former official website at openbugs.net is offline, a source code mirror can be found at Github/openbugs, but development appears to be shifted to MultiBugs with its source, also on GitHub as noted in the page Future Developments which still can be found on Internet Archive.

Worked examples

Example 1 — a first encounter with OpenBUGS

Start with the simplest possible case. Write down what OpenBUGS claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to OpenBUGS before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about OpenBUGS ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of OpenBUGS

In research
OpenBUGS appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses OpenBUGS in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
OpenBUGS is common in secondary-school and first-year university syllabi. It links to neighbouring topics Free Bayesian statistics software, Monte Carlo software, Numerical programming languages, so understanding it makes those chapters shorter.
In everyday life
Look for OpenBUGS outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study OpenBUGS in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what OpenBUGS means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain OpenBUGS out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is OpenBUGS in simple terms?

OpenBUGS is a software application for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. OpenBUGS is the open source variant of WinBUGS (Bayesian inference Using Gibbs Sampling).

Why does OpenBUGS matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study OpenBUGS?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on OpenBUGS.

Tags

  • Free Bayesian statistics software
  • Monte Carlo software
  • Numerical programming languages

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