- Acrobat
Reader: If you need the plug-in to read pdf
files (Acrobat Reader), click
**here**. - The R software package is available at no charge here.
- The winBUGS software is available at no charge here.

· Some of the software listed below is available in the form of shar files.

- Software to implement MCMC to estimate parameters for Bayesian model for estimating abundance when sighting data are acquired from distinct sampling occasions without replacement, but the exact number of marked individuals is unknown.
- This code was written by Brett McClintock [last updated 18/Nov/2008].
- An R version of the software is available here.
- An WinBUGS version of the software is available here.
- The paper that describes
this methodology: B. T. McClintock and J. A. Hoeting, “Bayesian
analysis of abundance for binomial sighting data with unknown number of
marked individuals,”
*Ecological and Environmental Statistics*, DOI 10.1007/s10651-009-0109-0.

- Software to perform Bayesian estimation for an autologistic model with covariates.
- S-Plus Code, C++ Code, and manual for C++ Code
- S-plus code written by
Jennifer Hoeting [last updated: 3/Jul/00]

[4/23/03: The Splus code needs revision as it uses Scompile which is no longer available. ] - C++ Code written by Greg Young [last updated: 22/Mar/01]. The manual is a pdf file.

- This winBUGS code performs Bayesian estimation for an AR(2) band recovery model.
- The code was written by Devin Johnson [last updated: 1/May/02].
- The paper that describes this methodology: Johnson, D. S. and J. A. Hoeting (2003) “Autoregressive Models for Capture-Recapture Data: A Bayesian Approach,” Biometrics, 59:340-349.

R code to perform Bayesian model averaging (BMA) to account for model uncertainty in linear regression models, GLMs, and survival models. This code was written by Adrian Raftery, Jennifer Hoeting, Chris Volinsky, Ian Painter, Ka Yee Yeung.

S-Plus code to perform Bayesian model averaging (BMA) to account for model uncertainty in linear regression models. Written by Jennifer Hoeting [last updated: 18/Apr/98]. This code is now part of the bma package in R (see above).

Software and references on Bayesian Model Averaging

- Software to compute AIC and MDL for geostatistical models for R.
- The code was written by Andrew Merton [last updated: 2/April/04].
- This project was supported by US EPA Science to Achieve Results (STAR) Program, CR - 829095.

- This winBUGS code comes in two parts: a saturated model (full dependence) for the response and the covariate model.
- The corresponding data are the saturated model data (full dependence) for the response and data for the covariate model data.
- The code was written by Devin Johnson [last updated: 15/August/2007].
- The paper that describes this methodology: Johnson, D. S., J. A. Hoeting, and B. S. Fadely (2007), “Random Effects Graphical Regression Models for Multidimensional Categorical Data,” submitted. <\ul>

- A set of XLISP-STAT functions to perform Bayesian Predictive Simultaneous Variable and Transformation Selection for regression. A criterion-based approach to model selection. This code was written by Jennifer Hoeting [last updated: 13/Dec/96].