WinBUGS User Manual - Department of Mathematics and Statistics

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1. WinBUGS User Manual - Department of Mathematics and Statistics

aie WinBUGS User Manual Version 1 4 January 2003 David Spiegelhalter Andrew Thomas Nicky Best Dave Lunn 1 MRC Biostatistics Unit Institute of Public Health Robinson Way Cambridge CB2 2SR UK 2 Department of Epidemiology amp Public Health Imperial College School of Medicine Norfolk Place London W2 1PG UK e mail bugs mrc bsu cam ac uk general andrew thomas ic ac uk technical internet http www mrc bsu cam ac uk bugs Permission and Disclaimer
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1. (2003). WinBUGS user manual 1.4

aie WinBUGS User Manual Version 1 4 January 2003 David Spiegelhalter Andrew Thomas Nicky Best Dave Lunn 1 MRC Biostatistics Unit Institute of Public Health Robinson Way Cambridge CB2 2SR UK 2 Department of Epidemiology amp Public Health Imperial College School of Medicine Norfolk Place London W2 1PG UK e mail bugs mrc bsu cam ac uk general andrew thomas ic ac uk technical internet http www mrc bsu cam ac uk bugs Permission and Disclaimer
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2. Winbugs

Winbugs Introduction This document is intended to introduce some basic information about Winbugs We hope by reading this introductory report users can have a first look at this statistical software and get familiar with Winbugs in a short time Most of the examples used in the report and function codes are coming from the user s manual of Winbugs What is Winbugs WinBUGS is statistical software for Bayesian analysis using Markov chain Monte Carlo MCMC methods It is ba
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3. Getting started with WinBUGS

Getting started with WinBUGS James B Elsner and Thomas H Jagger Department of Geography Florida State University Some material for this tutorial was taken from http www unt edu rss class rich 5840 session 1 doc 2 The BUGS Project Bayesian inference Using Gibbs Sampling i fe p i BUGS http www mrc bsu cam ac uk bugs Project The BUGS Project welcome Welcome Page Latest News Overview amp Demo WinBUGS New WinBUGS
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4. WinBUGS User Manual - Department of Mathematics and Statistics

aie WinBUGS User Manual Version 1 4 January 2003 David Spiegelhalter Andrew Thomas Nicky Best Dave Lunn 1 MRC Biostatistics Unit Institute of Public Health Robinson Way Cambridge CB2 2SR UK 2 Department of Epidemiology amp Public Health Imperial College School of Medicine Norfolk Place London W2 1PG UK e mail bugs mrc bsu cam ac uk general andrew thomas ic ac uk technical internet http www mrc bsu cam ac uk bugs Permission and Disclaimer
PDF Manual ENGLISH
5. Chapter 8: Using the WinBUGS interface in MlwiN

Using the WinBUGS interface in MLwiN Dr William Browne Centre for Multilevel Modelling Institute of Education London 22 October 2001 Background to MLwiN MLwiN is a statistical software package designed to fit multilevel models and developed at the Institute of Education It is the latest in a line of multilevel modelling packages developed over the last 15 years and forerunners include ML2 ML3 and MLN It is produced by a team of academics at the Institute under t
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6. Introduction to WinBUGS

em e AppendixBWinbugs fm Page 305 Friday August 27 2004 11 57 AM T Introduction to WinBUGS B 1 INTRODUCTION WinBUGS the MS Windows operating system version of BUGS Bayesian Analysis Using Gibbs Sampling is a versatile package that has been designed to carry out Markov chain Monte Carlo MCMC computations for a wide variety of Bayesian models The software is currently distributed electronically from the BUGS Project website The address is http www mrc bsu cam
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7. WinBUGS practicals (pdf file).

Introduction to Bayesian Inference Practical Exercises You will be using WinBUGS 1 4 1 for these practicals which you should have already installed on your PC All the data and other files you will need for the practicals were provided in a zip file which you should have unzipped and saved in the directory C data If you didn t receive this zip archive and or don t have WinBUGS installed on your PC please ask as we have a copy on a USB memory stick that you can inst
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8. WinBUGS: a tutorial

Overview WinBUGS a tutorial Anastasia Lykou and loannis Ntzoufras The reinvention of Markov chain Monte Carlo MCMC methods and their implementation within the Bayesian framework in the early 1990s has established the Bayesian approach as one of the standard methods within the applied quantitative sciences Their extensive use in complex real life problems has lead to the increased demand for a friendly and easily accessible software which implements Bayesian models
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