aggreCAT
Mathematically Aggregating Expert Judgments
The use of structured elicitation to inform decision making has grown dramatically in recent decades, however, judgements from multiple experts must be aggregated into a single estimate. Empirical evidence suggests that mathematical aggregation provides more reliable estimates than enforcing behavioural consensus on group estimates. 'aggreCAT' provides state-of-the-art mathematical aggregation methods for elicitation data including those defined in Hanea, A. et al. (2021) <doi:10.1371/journal.pone.0256919>. The package also provides functions to visualise and evaluate the performance of your aggregated estimates on validation data.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
2026-04-09 windows/windows R-4.5 | aggreCAT_1.0.0.zip |
1.4 MiB |