MAR Data

MAR Dat

Supplement 1. WinBUGS and R code to fit change point and variable selection models.

<h2>File List</h2><blockquote> <p><a href="trend model with changepoints.txt">trend model with changepoints.txt</a>  - WinBUGS model file for trend model with change points<br> <a href="R code to fit trend model with change-points.R">R code to fit trend model with change-points.R</a>  - R script for fitting trend model via R2WinBUGS<br> <a href="varselect model.txt">varselect model.txt</a>  - WinBUGS model file for non-linear variable selection model<br> <a href="R code to fit variable selection model.R">R code to fit variable selection model.R</a>  - R script for fitting variable selection model via R2WinBUGS<br> <a href="CCCP model.txt">CCCP model.txt</a>  - WinBUGS model file for covariate conditioned change point model<br> <a href="R code to fit cccp model.R">R code to fit cccp model.R</a>  - R script for fitting covariate conditioned change point model via R2WinBUGS<br> <a href="multispecies changepoint.txt">multispecies changepoint.txt</a>  - WinBUGS model file for multi-species covariate conditioned change point model<br> <a href="R code to fit multispecies cccp model.R">R code to fit multispecies cccp model.R</a>  - R script for fitting multi-species covariate conditioned change point model via R2WinBUGS<br> <a href="Data.zip">Data.zip</a>  - Data saved as R objects to demonstrate use of R scripts and WinBUGS models</p> <p><br> <a href="All files.zip">Download all files.zip</a> </p> </blockquote><h2>Description</h2><blockquote> <p>The .txt files are WinBUGS model codes for the models described in the paper. These models require the reversible "jump" add-on for WinBUGS (available from WinBUGS development website). The R scripts can be used to generate required data files and run the WinBUGS models from R. Data.zip contains example input data for all models. The R scripts require all files to be in the R working directory and the R2WinBUGS package must be installed.</p> </blockquote

Appendix A. Details of prior distributions used in change point and associated regression models.

Details of prior distributions used in change point and associated regression models

Appendix C. Details of parameter estimates for multivariate autoregressive (MAR) models underlain by Ricker and Gompertz population-dynamic formulations (only parameters with large odds ratios are listed).

Details of parameter estimates for multivariate autoregressive (MAR) models underlain by Ricker and Gompertz population-dynamic formulations (only parameters with large odds ratios are listed)

Appendix B. Details of parameter estimates for multivariate autoregressive (MAR) model with and without distinct variables suggested by other analyses (only parameters with large odds ratios are listed).

Details of parameter estimates for multivariate autoregressive (MAR) model with and without distinct variables suggested by other analyses (only parameters with large odds ratios are listed)

Appendix A. Details of parameter estimates for the multivariate autoregressive (MAR) model including credible intervals of odds ratios (all model parameters are listed).

Details of parameter estimates for the multivariate autoregressive (MAR) model including credible intervals of odds ratios (all model parameters are listed)