[logo]
The BUGS Project
The BUGS Project
Winbugs1.4 beta version
((((
Welcome Page
Latest News
Contact us/BUGS list
WinBUGS
New WinBUGS examples
The BUGS Book
FAQs
DIC
GeoBUGS
PKBUGS
Running from other software
BUGS resources online
WinBUGS development site
OpenBUGS site

New examples for WinBUGS

The following examples are in no particular order - please see BUGS resources on the web for a lot more examples provided by others.

1.4 only means that the example will not run in WinBUGS 1.3.

Example name and description Text file (either plain text or for decoding) .odc File
Hips: integrated evidence synthesis and cost-effectiveness analysis.
These programs accompany the paper: Spiegelhalter DJ and Best NB (2002) "Bayesian approaches to multiple sources of evidence and uncertainty in complex cost-effectiveness modelling" [PDF],
FunShapes: arbitrary constraints on functions of parameters
Attractive illustration of the `step trick'. Use the correlations tool to draw the pictures.
Hepatitis - measurement error on covariates
The example used in Chapter 2 of Gilks, Richardson and Spiegelhalter (1996)
Rats-drop - informative dropout
The old rats example, illustrating the impact of an informative dropout assumption.
Camel - multivariate normal with missing data
Tanner and Wong's example of structured missing data which gives a bimodal posterior for the correlation. 1.4 only
Pines - Bayes factors using the Carlin and Chib approach
The old example from the Classic BUGS Examples Vol 2, page 47.
Jama - use of the interp-lin function in radiocarbon calibration.
Example provided by Andrew Millard. 1.4 only
StVeit - radiocarbon calibration with stratification.
Example provided by Andrew Millard. 1.4 only
Eye-tracking - Dirichlet process prior for mixture of Poissons
Adapted from Congdon (2001), Ex 6.27, to allow learning of baseline distribution.. 1.4 only
Pigweights - Non-wishart prior on MVN precision matrix
Histogram smoothing using a multinomial-logistic model, with autoregressive random effects. Illustrates use of structured precision matrix (and also struictured covariance matrix,m but this is very slow due to need for matrix inversions). Adapted from Congdon (2001), Ex 5.9. 1.4 only


© 1996-2012 BUGS
Hosted by the MRC Biostatistics Unit, Cambridge, UK
Site designed by Alastair Stevens
TOP