Bayesian Composition Sampling
August 16, 2024
R Code to Run Composition Sampling for Cook et al. 2023
The aim of this software is to perform composition sampling on simulated disease observation data. Composition sampling is a valuable approach for statistical inference in data limited systems. This software implements composition sampling on simulated chronic wasting disease surveillance data in white-tailed deer in Michigan, U.S.
For additional detail on the methodology and case study, we refer the reader to Cook, J.D., Williams, D.M., Walsh, D.P., and Hefley, T.J. 2023. Bayesian forecasting of disease spread with little or no data.
Citation Information
| Publication Year | 2024 |
|---|---|
| Title | Bayesian Composition Sampling |
| DOI | 10.5066/P9XMF7FS |
| Authors | Jonathan D Cook |
| Product Type | Software Release |
| Record Source | USGS Asset Identifier Service (AIS) |
| USGS Organization | Eastern Ecological Science Center at the Leetown Research Laboratory |